Guidance Inventory — Core Reference

Graph-native guidance extraction system. Writes Guidance and GuidanceUpdate nodes to Neo4j. No markdown output, no file accumulation.

Thinking: ALWAYS use ultrathink for maximum reasoning depth when extracting and classifying guidance.

NON-EXHAUSTIVE LISTS: Every list in this document (metrics, keywords, concepts, instant labels) is a starting set of common examples — NOT a filter. Extract guidance for ANY metric you find, even if unlisted. Create new labels freely. Set xbrl_qname=null when no concept matches.

Table of Contents

1. Graph Schema
2. Extraction Fields
3. Deterministic IDs
4. Metric Normalization
5. Derivation Rules
6. Basis Rules
7. Segment Rules
8. Unit Canonicalization
9. Period Resolution
10. Company + Period Resolution
11. XBRL Matching
12. Source Processing
13. Quality Filters
14. Chronological Ordering
15. Write Path
16. Execution Modes
17. Error Taxonomy
18. Reference Files

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1. Graph Schema

Nodes

Created by guidance: Guidance (generic metric tag), GuidanceUpdate (per-mention data point), GuidancePeriod (calendar-based, gp_ namespace) Reused (MATCH only): Company, Concept, Member, Report / Transcript / News Removed: Context (replaced by direct FOR_COMPANY edge), Unit (demoted to canonical_unit property)

Relationship Map (6 edges)

From	Rel	To	When
GuidanceUpdate	UPDATES	Guidance	Always
GuidanceUpdate	FROM_SOURCE	Report / Transcript / News	Always (provenance)
GuidanceUpdate	FOR_COMPANY	Company	Always (direct, replaces Context)
GuidanceUpdate	HAS_PERIOD	GuidancePeriod	Always (calendar-based, 1:1 cardinality)
GuidanceUpdate	MAPS_TO_CONCEPT	Concept	0..1 when xbrl_qname resolves
GuidanceUpdate	MAPS_TO_MEMBER	Member	0..N confident segment matches

Constraints

CREATE CONSTRAINT guidance_id_unique IF NOT EXISTS
FOR (g:Guidance) REQUIRE g.id IS UNIQUE;

CREATE CONSTRAINT guidance_update_id_unique IF NOT EXISTS
FOR (gu:GuidanceUpdate) REQUIRE gu.id IS UNIQUE;

CREATE CONSTRAINT guidance_period_id_unique IF NOT EXISTS
FOR (gp:GuidancePeriod) REQUIRE gp.id IS UNIQUE;

Sentinel nodes (pre-created via create_guidance_constraints()):

(:GuidancePeriod {id: 'gp_ST',    u_id: 'gp_ST',    start_date: null, end_date: null})
(:GuidancePeriod {id: 'gp_MT',    u_id: 'gp_MT',    start_date: null, end_date: null})
(:GuidancePeriod {id: 'gp_LT',    u_id: 'gp_LT',    start_date: null, end_date: null})
(:GuidancePeriod {id: 'gp_UNDEF', u_id: 'gp_UNDEF', start_date: null, end_date: null})

Guidance Node Properties

Property	Type	Description
id	String	guidance:{slug(label)}
label	String	Normalized metric name
aliases	String[]	Alternate names
created_date	String	ISO date when first detected

GuidanceUpdate Node Properties

All 20 extraction fields (see §2) plus system identity properties:

Property	Type	Description
id	String	Deterministic key (see §3)
evhash16	String	First 16 hex chars of evidence hash
xbrl_qname	String / null	Resolved XBRL concept qname (see §11)
concept_family_qname	String / null	Canonical XBRL concept family anchor (CLI-computed, do not set)
unit_raw	String / null	Verbatim unit text, only when canonical_unit='unknown'
label	String	Metric name (denormalized from Guidance parent)
label_slug	String	slug(label) — enables WHERE gu.label_slug = 'revenue' without JOIN
segment_slug	String	slug(segment) — enables WHERE gu.segment_slug = 'iphone'
source_refs	String[]	IDs of sub-source nodes (e.g., QAExchange IDs for transcripts). Empty array if none.

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2. Extraction Fields

Every GuidanceUpdate carries these 20 properties. System identity properties (id, evhash16) are added at write time.

#	Field	Type	Constraint	Example
1	given_date	String	ISO date	"2025-01-30"
2	period_scope	String	quarter, annual, half, monthly, long_range, short_term, medium_term, long_term, undefined	"quarter"
3	time_type	String	duration (default ~99%), instant (balance-sheet items only)	"duration"
4	fiscal_year	Integer		2025
5	fiscal_quarter	Integer / null	1-4; null for annual	2
6	segment	String	Default "Total"	"Services"
7	low	Float / null		94.0
8	mid	Float / null	Computed if low+high given	95.5
9	high	Float / null		97.0
10	canonical_unit	String	Canonical: usd, m_usd, percent, percent_yoy, percent_points, basis_points, x, count, unknown (see §8)	"m_usd"
11	basis_norm	String	gaap, non_gaap, constant_currency, unknown	"non_gaap"
12	basis_raw	String / null	Verbatim basis text	"adjusted"
13	derivation	String	See §5	"calculated"
14	qualitative	String / null	What management expects (the prediction itself)	"low to mid single digits"
15	quote	String	Max 500 chars, verbatim	"We expect revenue between..."
16	section	String	Location within source	"CFO Prepared Remarks"
17	source_key	String	Sub-document key	"EX-99.1", "full", "title", "MD&A"
18	conditions	String / null	Stated "if/assuming/excluding" caveats that qualify it	"assumes no further rate hikes"
19	source_type	String	8k, transcript, news, 10q, 10k	"transcript"
20	created	String	ISO timestamp of node creation	"2026-02-18T14:30:00Z"

Rule: No citation = no node. Every GuidanceUpdate MUST have quote, FROM_SOURCE, and given_date.

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3. Deterministic IDs

No UUIDs, no sequences. All writes use MERGE on id.

Guidance ID

guidance_id = "guidance:" + slug(label)

slug() = lowercase, trim, replace non-alphanumeric with _, collapse repeated _, trim edge _.

GuidanceUpdate ID

guidance_update_id = "gu:" + source_id + ":" + label_slug + ":" + period_u_id
                     + ":" + basis_norm + ":" + segment_slug

The ID is the slot — it identifies WHICH guidance item, not WHAT it says. One node per metric per source per period per basis per segment. No value hash in the ID.

Evidence Hash (stored property, not in ID)

evhash16 = sha256("{low}|{mid}|{high}|{unit}|{qualitative}|{conditions}")[:16]

Stored as gu.evhash16 property for query-time change detection across sources. NOT part of guidance_update_id.

Rules:

• Numeric parts: canonical decimal strings after unit normalization
• Aggregate currency metrics normalize to m_usd before hashing
• Per-share currency metrics (EPS, DPS) normalize to usd
• Percentages normalize to percent or percent_yoy
• unit is lowercase canonical enum value
• Text parts: lowercase + trimmed + whitespace-collapsed
• Nulls encoded as . (dot)

Canonicalization Before ID Build

Component	Rule
source_id	Trim whitespace. If contains :, replace with _ for delimiter safety.
label_slug	label.lower().replace(" ", "_")
segment_slug	segment.lower().replace(" ", "_") (default total)
basis_norm	Enum as-is: gaap|non_gaap|constant_currency|unknown
period_u_id	Calendar-based: gp_YYYY-MM-DD_YYYY-MM-DD or sentinel gp_ST/gp_MT/gp_LT/gp_UNDEF

Idempotency & Enrichment

• Same source + same slot = same id → MERGE matches → SET updates properties (latest write wins)
• Same source + same metric but different period/basis/segment = different id
• Different source + same metric = different id (different source_id)
• Re-run with richer data → same ID → properties overwritten with better values

Implementation

Use guidance_ids.py:build_guidance_ids() as single entry point. Do not duplicate ID logic.

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4. Metric Normalization

12 canonical metrics below are common examples — create new base metrics freely for any company-specific or industry-specific metric not listed here.

Standard Label	Variants
Revenue	revenue, sales, net revenue, total revenue, net sales
EPS	EPS, earnings per share, diluted EPS
Gross Margin	gross margin, GM, gross profit margin
Operating Margin	operating margin, op margin
Operating Income	operating income, income from operations
Net Income	net income, net earnings, bottom line
OpEx	operating expenses, SG&A, R&D + SG&A
Tax Rate	effective tax rate, tax rate, provision for income taxes
CapEx	capital expenditures, capex, capital spending
FCF	free cash flow, operating cash flow minus capex
OINE	other income and expense, other income/expense net
D&A	depreciation and amortization, D&A, depreciation

Aliases are stored on the Guidance node in aliases[]. Non-exhaustive — new base metrics not in this table (e.g., "Installed Base", "ARPU") are created as-is with segment="Total" (see "No qualifier" in Metric Decomposition below).

Metric Decomposition

When source text qualifies a metric, split into label (the base metric) + segment (the qualifier):

Decompose when the qualifier names a business dimension — a product, geography, business unit, or customer type:

• "iPhone Revenue" → label="Revenue", segment="iPhone"
• "North America Operating Income" → label="Operating Income", segment="North America"
• "Cloud Services Gross Margin" → label="Gross Margin", segment="Cloud Services"

Do NOT decompose when the qualifier is an accounting or measurement modifier — it changes what is being measured, not who/where:

• "Cost of Revenue" → label="Cost of Revenue", segment="Total" (different metric than Revenue)
• "Adjusted EBITDA" → label="Adjusted EBITDA", segment="Total"
• "Pro Forma EPS" → label="Pro Forma EPS", segment="Total"

No qualifier — just "Revenue" or "EPS" — set label to the metric as-is, segment="Total".

Simple test: Could you have this metric for iPhone AND for Total? If yes, the prefix is a segment — decompose. If the prefix changes the financial definition, keep it whole.

No-match is OK: If a qualifier doesn't match any Member node, still decompose. Member matching (§7) handles no-match gracefully.

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5. Derivation Rules

Derivation	When	Example	Numeric Fields
explicit	Company states exact range	"revenue of $94-97B"	low, mid, high populated
calculated	Derived from stated values	GM% = guided gross profit / guided revenue	low, mid, high computed
point	Single number, no range	"CapEx of approximately $2B"	low = mid = high
implied	Qualitative or partial info	"low to mid single digits"	low/mid/high null; qualitative populated
floor	Lower bound only	"at least $150M"	low=150, mid/high null
ceiling	Upper bound only	"up to $500M"	high=500, low/mid null
comparative	Relative/anchor phrasing	"roughly in line with Q2"	Numeric fields null; anchor in qualitative/conditions

Rules:

• floor/ceiling do NOT force fabricated midpoints
• comparative keeps numeric fields null unless explicitly stated
• When derivation=calculated and a range is given: mid = (low + high) / 2
• When derivation=implied: never invent numeric values

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6. Basis Rules

Assignment Rule

basis_norm is assigned ONLY when the basis qualifier is explicit in the same sentence/span as the guidance value. Otherwise default to unknown.

Canonical Values

basis_norm	Maps From
gaap	GAAP, as reported, as-reported
non_gaap	non-GAAP, adjusted, excluding special items, core
constant_currency	constant currency, FX-neutral
unknown	No explicit qualifier in quote span

Tracking

• basis_norm: canonical enum value (stored, used in ID)
• basis_raw: verbatim qualifier text from source (stored, not in ID)

Trap: Implicit Basis Switches

CFO may switch between GAAP and non-GAAP within the same paragraph. Each metric gets its own basis determination from its own quote span:

"On a GAAP basis, we expect EPS of $3.20. And revenue should be about $95 billion."

Here: EPS = gaap, Revenue = unknown (no explicit qualifier for revenue).

Query-Time Safety

Mixed bases may appear in the same metric history. Never compare consecutive values without filtering by basis_norm first.

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7. Segment Rules

Defaults

• Default segment: Total (company-wide, no qualifier)
• Assign segment when source text qualifies a metric with any dimensional qualifier (product, geography, business unit, etc.)

Extraction

After decomposition (§4), each qualifier becomes a segment label. Set member_u_ids: [] — the CLI resolves members at write time (see below).

Member Matching (CLI-Owned)

Member resolution is handled entirely by guidance_write_cli.py at write time. Agents set member_u_ids: [].

1. Warmup builds a CIK-based member map (/tmp/member_map_{TICKER}.json) — all Member nodes for the company by CIK prefix
2. CLI normalizes each item's segment text: lowercase, strip whitespace, remove member/segment tokens, light singularization (services→service, products→product, accessories→accessory)
3. Exact normalized match → populates member_u_ids with matching u_id(s)
4. No match → no edge. Segment text preserved regardless.
5. In write mode, if precomputed map is missing, falls back to live CIK query (self-healing)

Multi-Axis

• Members from different axes (e.g., product + geography) are valid together
• segment stores human-readable text; member_u_ids stores graph links — they're related but independent

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8. Unit Canonicalization

Canonical Units

usd, m_usd, percent, percent_yoy, percent_points, basis_points, x, count, unknown

Alias Map

Raw	Canonical
$, dollars	m_usd (per-share labels like EPS/DPS override to usd)
b usd, b_usd, billion	m_usd
m usd, million	m_usd
%, pct	percent
% yoy, yoy	percent_yoy
bps, bp	basis_points
% points, pp, percentage points	percent_points
times, multiple	x

Scale Normalization

• Aggregate currency metrics (Revenue, Net Income, OpEx, CapEx, FCF, etc.) normalize to m_usd
• Per-share metrics (EPS, DPS) normalize to usd
• $1.13B and 1130 M USD both → 1130 in m_usd
• Percentages → percent or percent_yoy only

Unknown Handling

No alias match → canonical_unit = 'unknown', raw unit preserved in unit_raw property on GuidanceUpdate. unit_raw is NOT part of evhash16 (canonical canonical_unit is used).

Implementation

Use guidance_ids.py:canonicalize_unit(). Adding new units: one entry in CANONICAL_UNITS + alias(es) in UNIT_ALIASES + test case.

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9. Period Resolution

GuidancePeriod — Calendar-Based, Company-Agnostic

Every GuidanceUpdate has exactly ONE HAS_PERIOD edge to a GuidancePeriod node. GuidancePeriod uses calendar dates (month boundaries), not fiscal keys. Company-agnostic — two companies covering the same calendar window share the same node.

period_scope Enum (9 values)

period_scope	GuidancePeriod	Example u_id	Example text
quarter	Real calendar dates	gp_2025-04-01_2025-06-30	"Q3 revenue of $85B"
annual	Real calendar dates	gp_2024-10-01_2025-09-30	"FY2025 CapEx of $30B"
half	Real calendar dates	gp_2025-04-01_2025-09-30	"Second half margin expansion"
monthly	Real calendar dates	gp_2025-03-01_2025-03-31	"March same-store sales"
long_range	Real calendar dates	gp_2026-01-01_2028-12-31	"By 2028", "2026-2028 target"
short_term	Sentinel gp_ST	gp_ST	"In the near term"
medium_term	Sentinel gp_MT	gp_MT	"Over the medium term"
long_term	Sentinel gp_LT	gp_LT	"Long-term target model of 38-40%"
undefined	Sentinel gp_UNDEF	gp_UNDEF	"Going forward" (no temporal anchor)

First 5 require _compute_fiscal_dates(). Last 4 always use sentinels with null dates.

Python Routing (LLM fields -> period_scope -> calendar dates)

Python evaluates LLM extraction fields in priority order. First match wins:

1. sentinel_class set? -> period_scope = sentinel_class, u_id = gp_{abbreviation}
2. long_range_end_year set? -> period_scope = "long_range", compute via _compute_fiscal_dates()
3. month set? -> period_scope = "monthly", {year}-{month}-01 to {year}-{month}-{last_day}
4. half set? -> period_scope = "half", compose from two quarter calls
5. fiscal_quarter set? -> period_scope = "quarter", _compute_fiscal_dates(fye, fy, Qn)
6. fiscal_year set (no quarter)? -> period_scope = "annual", _compute_fiscal_dates(fye, fy, "FY")
7. Fallthrough -> period_scope = "undefined", u_id = "gp_UNDEF"

At every step: fye = 12 if calendar_override else company_fye_month.

For instant items (time_type == "instant" or label in known instant set): start_date = end_date (period's end date).

Implementation: guidance_ids.py:build_guidance_period_id(). Do NOT build period IDs manually.

GuidancePeriod Node Properties

Property	Type	Notes
id	String	Same as u_id (MERGE key, has uniqueness constraint)
u_id	String	gp_{start}_{end} or gp_ST/gp_MT/gp_LT/gp_UNDEF
start_date	String / null	ISO date, null for sentinels
end_date	String / null	ISO date, null for sentinels

Fiscal Context Rule

In earnings calls and SEC filings, ALL period references are fiscal unless explicitly stated as calendar. "Second half" = fiscal H2. Only use calendar interpretation when text explicitly says "calendar year/quarter" — set calendar_override: true.

Calendar-to-Fiscal Mapping

Rule: Q1 starts in FYE month + 1. When source says "Q1" or "Q2" explicitly, use as-is.

FYE Month	Example	Q1	Q2	Q3	Q4
9 (Sep)	Apple	Oct-Dec	Jan-Mar	Apr-Jun	Jul-Sep
12 (Dec)	Most	Jan-Mar	Apr-Jun	Jul-Sep	Oct-Dec
6 (Jun)	Microsoft	Jul-Sep	Oct-Dec	Jan-Mar	Apr-Jun

---

10. Company + Period Resolution (v3.1)

Architecture (v3.1 — GuidancePeriod)

No Context node. No Unit node. Direct edges from GuidanceUpdate:

• FOR_COMPANY → Company (matched by ticker, replaces IN_CONTEXT → Context → FOR_COMPANY)
• HAS_PERIOD → GuidancePeriod (calendar-based, gp_ namespace)
• canonical_unit is a property on GuidanceUpdate (not a separate node)

Steps

1. FYE: Query 1B (QUERIES.md) → extract FYE month from periodOfReport
2. Period: build_guidance_period_id(fye_month, fiscal_year, fiscal_quarter, ...) → gp_ format
   - Or: pass LLM fields in JSON payload, CLI computes period via _ensure_period()
3. Unit: canonicalize_unit(unit_raw, label_slug) → stored as gu.canonical_unit property
4. MERGE GuidancePeriod + GuidanceUpdate + edges (via guidance_writer.py)

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11. XBRL Matching

All linking is inline in the same extraction run. Mapping failures never block core writes.

Concept Resolution (sets xbrl_qname + MAPS_TO_CONCEPT edge)

Dual approach: MAPS_TO_CONCEPT edge (graph-native join to XBRL Concept) + xbrl_qname property (cross-taxonomy fallback). Both set at extraction time.

Why both: The edge enables graph-native joins between guidance and actuals via Concept nodes. The xbrl_qname property provides a stable cross-taxonomy fallback — same logical concept has separate Concept nodes per year, but qname never changes. If no Concept node matches, the edge is silently skipped (MATCH fails) but xbrl_qname is still written.

Concept Pattern Map

Guidance Label	qname include	qname exclude
Revenue	Revenue	RemainingPerformanceObligation
EPS	EarningsPerShareDiluted	—
Gross Margin	GrossProfit	—
Operating Margin	—	— (derived, no concept)
Operating Income	OperatingIncomeLoss	—
Net Income	NetIncome, ProfitLoss	—
OpEx	OperatingExpenses	—
Tax Rate	EffectiveIncomeTaxRate	—
CapEx	PaymentsToAcquirePropertyPlantAndEquipment	—
FCF	—	— (derived, no concept)
OINE	OtherNonoperatingIncomeExpense	—
D&A	DepreciationAmortization	—

This maps the 12 common metrics. For metrics not in this table, set xbrl_qname=null — do NOT skip the item or force-fit it into a listed concept.

Concept Resolution Gate

1. Pattern-match against concept usage cache (QUERIES.md query 2A)
2. Exactly one match → use it
3. Multiple matches → highest usage count wins
4. Zero matches → xbrl_qname = null
5. Mapping is basis-independent (GAAP, non-GAAP, unknown all get mapped)
6. Set via ON CREATE SET only
7. Concept resolution uses the base metric label after §4 decomposition, not the qualified name

Member Matching Gate

1. Extract segment candidates from quote/LLM output
2. Normalize both sides (see §7)
3. Match against member profile cache (QUERIES.md query 2B)
4. Write MAPS_TO_MEMBER edge only for confident matches
5. Allow 0..N member edges per GuidanceUpdate

Warmup Caches

Run once per company per extraction run. See QUERIES.md queries 2A (concept cache) and 2B (member cache).

---

12. Source Processing

Source Types and Richness

Source	Richness	Extract?
Transcript	Highest	YES — full scan (PR + Q&A)
8-K EX-99.* + Item text	High	YES — outlook/tables/footnotes
News	Medium	YES — after channel filter
10-Q/10-K MD&A	Low	YES — MD&A primary, bounded fallback
XBRL	None	NO — actuals only

Routing

Extraction MUST route by source_type before LLM processing. Each type has different scan scope and noise profiles. Per-source profiles in reference/:

Source Type	Profile
transcript	PROFILE_TRANSCRIPT.md
8k	PROFILE_8K.md
news	PROFILE_NEWS.md
10q, 10k	PROFILE_10Q.md

Source Type Mapping

source_type	source_key	given_date source
8k	"EX-99.1", "Item 2.02", "Item 7.01"	r.created
transcript	"full"	t.conference_datetime
news	"title"	n.created
10q	"MD&A"	r.created
10k	"MD&A"	r.created

Guidance Keywords

Category	Keywords
Forward-looking	expects, anticipates, projects, forecasts, outlook, looking ahead
Guidance	guidance, range, target, between X and Y, approximately
Periods	Q1-Q4, full year, fiscal year, FY, for the quarter, second half
Metrics	EPS, earnings per share, revenue, sales, margin, income, cash flow
Revisions	raises, lowers, maintains, reaffirms, withdraws, narrows, widens
Qualitative	low single digits, double-digit, mid-teens, high single digits
Conditional	assumes, contingent on, excluding, subject to

These keywords are common signals, not an exhaustive filter. Extract guidance regardless of whether the source text uses these specific words.

Dedup Rule

Deterministic slot-based GuidanceUpdate.id enforces dedup. Same slot = same ID → MERGE + SET updates properties.

Transcripts: Two-invocation extraction — PR via guidance-extract, Q&A enrichment via guidance-qa-enrich. MERGE+SET handles second write safely.

All other source types: Read all content first, extract the richest version per metric, write once per slot.

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13. Quality Filters

Applied AFTER extraction, BEFORE writing to graph:

Filter	Rule
Forward-looking only	Target period must be after source date. Past-period results are actuals, not guidance.
Specificity required	Qualitative guidance needs a quantitative anchor: "low single digits", "double-digit", "mid-teens". Skip vague terms ("significant", "strong") without magnitude.
No fabricated numbers	If guidance is qualitative, use derivation=implied/comparative. Never invent numeric values.
Quote max 500 chars	Truncate at sentence boundary with "..." if needed.
100% recall priority	When in doubt, extract it. False positives > missed guidance.
News: company guidance only	Ignore analyst estimates ("Est $X", "consensus $Y"). Extract only company-issued guidance.
Factors are conditions, not items	If a forward-looking statement quantifies a factor affecting another guided metric (e.g., FX headwind, week count, commodity cost tailwind), capture it in that metric's conditions field — not as a standalone item. A factor already captured in a metric's conditions field is already extracted — do not also create a standalone item for it.
Material corporate announcements	Extract management decisions that allocate specific capital or change shareholder returns (e.g., buyback authorizations, dividend declarations, major investment programs). These are announced actions, not forecasts — use derivation=explicit or derivation=point for stated amounts, derivation=comparative for directional changes. Apply the same specificity rules: a quantitative anchor is required.

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14. Chronological Ordering

GuidanceUpdate nodes do NOT maintain NEXT/PREVIOUS edges.

Ordering Rule

All time-based reads MUST use:

ORDER BY gu.given_date, gu.id

Or latest-first:

ORDER BY gu.given_date DESC, gu.id DESC

No linked-list maintenance. No supersession chains. No action classification storage. Latest by given_date (tie-break id) is current. First in timeline is implicit anchor.

---

15. Write Path

Extraction Pipeline

1. LOAD CONTEXT
   ├── Company + CIK (QUERIES.md 1A)
   ├── FYE from 10-K (QUERIES.md 1B)
   ├── Warmup caches (QUERIES.md 2A, 2B)
   └── Existing Guidance tags (QUERIES.md 7A)

2. LLM EXTRACTION (routed by source_type profile)
   ├── Fetch source content (QUERIES.md §3-§6)
   ├── Route to per-source profile (reference/PROFILE_*.md)
   ├── Feed: source content + existing Guidance tags + member candidates
   └── Extract: quote, period intent, basis, metric, values, derivation, XBRL candidates

3. DETERMINISTIC VALIDATION (pre-write)
   ├── Canonicalize unit + numeric scale (guidance_ids.py)
   ├── Validate basis rule (explicit-only)
   ├── Build period via build_guidance_period_id() or pass LLM fields for CLI routing
   ├── Resolve xbrl_qname from concept cache
   ├── Apply member confidence gate
   └── Uncertain? Keep core write, set xbrl_qname=null, skip member edges

4. PER ITEM: WRITE TO GRAPH (via guidance_writer.py)
   ├── Compute IDs (guidance_ids.py:build_guidance_ids)
   ├── MERGE Guidance node
   ├── MERGE GuidancePeriod (calendar-based, gp_ namespace)
   ├── MERGE GuidanceUpdate + edges (UPDATES, FROM_SOURCE, FOR_COMPANY, HAS_PERIOD)
   └── Link XBRL concept + members if confident

Idempotency & Enrichment

Compute deterministic slot-based ID first, then MERGE + SET. If node exists, properties are updated with latest extraction (latest write wins). No pre-check queries needed. No delete-before-rerun needed.

Reprocessing

Only needed if you want to remove ALL prior extractions and start fresh. Delete all GuidanceUpdates for a company → re-run initial build. Source documents remain in Neo4j. For normal re-runs, MERGE + SET handles enrichment automatically.

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16. Execution Modes

Invocation

/guidance-inventory {TICKER} {SOURCE_TYPE} {SOURCE_ID}
/guidance-inventory {TICKER} initial

Parameter	Type	Examples
TICKER	String	AAPL, MSFT
SOURCE_TYPE	Enum	8k, transcript, news, 10q, 10k, initial
SOURCE_ID	String	0001193125-25-000001, AAPL_2025-07-31T..., bzNews_50123456

Mode Parameter

Mode	Behavior
dry_run (default)	Extract + validate + ID build. Log to stdout. No writes.
shadow	Same as dry_run + log exact MERGE Cypher with parameters.
write	Full execution. MERGE to Neo4j.

Two-Layer Write Gate

1. MODE parameter (per-invocation) → maps to dry_run in write_guidance_item()
2. ENABLE_GUIDANCE_WRITES (global feature flag, default False) → checked after dry_run, before write

Both must be permissive for writes to occur. MODE=write with ENABLE_GUIDANCE_WRITES=False still blocks.

Must-Pass Gates Before Enabling Writes

1. test_guidance_ids.py passes
2. Shadow run on 3+ companies and 3+ source types
3. Idempotency: same source twice → zero new nodes on second run
4. Regression: existing ingest behavior unchanged
5. Canary: 1-2 tickers first, then full rollout

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17. Error Taxonomy

Error	When
SOURCE_NOT_FOUND	No rows from source content query
EMPTY_CONTENT	Rows exist but content empty (rules per source type below)
QUERY_FAILED	Cypher error
NO_GUIDANCE	Content parsed, no forward-looking guidance found
WRITE_FAILED	Graph MERGE error
VALIDATION_FAILED	Missing citation, bad period, invalid unit

Empty-Content Rules per Source Type

Source Type	Empty Condition
8k (exhibit/section/filing_text)	strip() == ""
transcript	BOTH prepared_remarks empty AND qa_exchanges empty
news	BOTH title and body empty
10q/10k	MD&A section strip() == ""

Handling

• SOURCE_NOT_FOUND or EMPTY_CONTENT: log error code + source details, return
• NO_GUIDANCE: acceptable — not all filings contain guidance
• WRITE_FAILED: log error, do not retry automatically
• VALIDATION_FAILED: log details, skip item, continue with remaining

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18. Reference Files

File	Purpose
QUERIES.md	Read-only Cypher reference (~42 queries)
reference/PROFILE_TRANSCRIPT.md	Transcript extraction profile
reference/PROFILE_8K.md	8-K extraction profile
reference/PROFILE_NEWS.md	News extraction profile
reference/PROFILE_10Q.md	10-Q/10-K extraction profile

Utility Scripts

Script	Purpose
guidance_ids.py	ID normalization, unit canonicalization, evhash16, build_guidance_period_id(), build_period_u_id() (deprecated)
guidance_writer.py	Direct Cypher write path (MERGE patterns, param assembly, validation)
guidance_write_cli.py	CLI entry point: reads JSON, computes IDs, calls guidance_writer.py
guidance_write.sh	Shell wrapper: activates venv, sets Neo4j env vars matching MCP server

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Additive Implementation Note (2026-03-09)

This note is intentionally additive and does not replace the member-matching rules above.

Member Matching Authority

• Query 2B member matching is a best-effort extraction aid.
• It is not the final authority for write-mode member identity.
• In write mode, guidance_write_cli.py may re-resolve and overwrite member_u_ids using company-wide Member lookup by CIK prefix plus Python normalization.

Why This Note Exists

• Runtime issue E4d showed that large member-cache reads can still truncate.
• Issue #61 showed that 2B-only/context-derived member lookup was not sufficient for all real members.
• Therefore the final authority must stay in the write path rather than the prompt.

Operational Rule

• Preserve segment text even when member_u_ids cannot be filled confidently.
• Leave member_u_ids empty rather than guessing.
• Treat MAPS_TO_MEMBER edges as write-path-resolved, not prompt-guaranteed.

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Version 3.1 | 2026-02-26 | v3.1: GuidancePeriod replaces Period — calendar-based (gp_ namespace), company-agnostic, with sentinel nodes (gp_ST/MT/LT/UNDEF). period_type renamed to period_scope (9-value enum). Added time_type field (duration/instant). build_guidance_period_id() replaces build_period_u_id(). fiscal_math.py extracted for clean imports. Prior: v3.0 (removed Context/Unit nodes, 6 edges, fiscal-keyed Period). v2.5 (MAPS_TO_CONCEPT). v2.3 (metric decomposition, segment rules).