Valuein — SEC EDGAR Fundamentals & Smart-Money Data

Score Due Claims (bulk auto-grader)

score_due_claims

Find every auto-gradable claim that is due (assertions in open/needs_review/stale; predictions whose horizon has passed) and resolve each against fundamentals. Operates on the caller's OWN claims — omit customer_id. Targeting another user's customer_id is reserved for Valuein's internal scoring service and is rejected for every plan, including Institutional. Returns a summary + per-claim results. Idempotent — re-calling only re-resolves what changed.

Input Schema

TableJSON Schema

Name	Required	Description
`max`	No	Soft cap on claims scored per call (default 100).
`as_of`	No	Snapshot date for the fundamentals window. Defaults to today UTC.
`customer_id`	No	Target user's Stripe customer_id. Defaults to the caller's own — leave it unset. Supplying a DIFFERENT customer_id is restricted to Valuein's internal scoring service and is rejected on every plan, Institutional included.

Output Schema

TableJSON Schema

Name	Required	Description
`due`	Yes
`_meta`	Yes	Provenance envelope — data lineage for every MCP response
`errors`	Yes
`scored`	Yes	Resolved to confirmed/refuted.
`results`	Yes
`scanned`	Yes
`skipped`	Yes
`needs_review`	Yes	Could not be auto-resolved; flagged for review.
`target_customer_id`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedSep 18, 2026

changedOutput schema / properties / _meta / properties / fundamentals_as_of / description

Previous value: -"ISO timestamp when the FINANCIAL STATEMENTS were last rebuilt. Use THIS — not `last_updated` — when telling a user how current the fundamentals are. The snapshot is republished on every weekday price refresh while the statements are carried forward unchanged, so `last_updated` can be far more recent than the numbers it sits next to."New value: +"ISO timestamp when the FINANCIAL STATEMENTS were last rebuilt in bulk. Use THIS — not `last_updated` — when telling a user how current the cross-sectional fundamentals are. The snapshot is republished on every weekday price refresh while the statements are carried forward unchanged, so `last_updated` can be far more recent than the numbers it sits next to. It is a floor for a single filer, not a ceiling: a filer with a live partition receives its filing, facts and ratios intraday (minutes after EDGAR dissemination), so an entity-scoped read may carry a filing newer than this; cross-sectional ranks (factor scores, earnings signals) refresh with the weekly bulk export."

Changed1 schema field changedAug 1, 2026

changedInput schema / properties / customer_id / description

Previous value: -"Target user's Stripe customer_id. Defaults to caller; requires `full` tier to target others."New value: +"Target user's Stripe customer_id. Defaults to the caller's own — leave it unset. Supplying a DIFFERENT customer_id is restricted to Valuein's internal scoring service and is rejected on every plan, Institutional included."

Changed2 schema fields changedJul 25, 2026

addedOutput schema / properties / _meta / properties / fundamentals_as_of

Added value: +{
+  "description": "ISO timestamp when the FINANCIAL STATEMENTS were last rebuilt. Use THIS — not `last_updated` — when telling a user how current the fundamentals are. The snapshot is republished on every weekday price refresh while the statements are carried forward unchanged, so `last_updated` can be far more recent than the numbers it sits next to.",
+  "type": "string"
+}

addedOutput schema / properties / _meta / properties / price_as_of

Added value: +{
+  "description": "ISO timestamp when the price surfaces were last refreshed.",
+  "type": "string"
+}

Changed2 schema fields changedJul 7, 2026

addedOutput schema / properties / _meta / properties / cost_usd

Added value: +{
+  "additionalProperties": false,
+  "description": "Per-call cost transparency. Omitted for subscription-only tools that have no PAYG-equivalent price.",
+  "properties": {
+    "amount_usd": {
+      "minimum": 0,
+      "type": "number"
+    },
+    "basis": {
+      "description": "payg_charge = real agent-pay charge. payg_rate_card = indicative price, not billed.",
+      "enum": [
+        "payg_charge",
+        "payg_rate_card"
+      ],
+      "type": "string"
+    },
+    "billed": {
+      "description": "true = this amount was actually charged via PAYG for this call. false = indicative PAYG-equivalent value; your plan already covers this call for free.",
+      "type": "boolean"
+    }
+  },
+  "required": [
+    "amount_usd",
+    "billed",
+    "basis"
+  ],
+  "type": "object"
+}

addedOutput schema / properties / _meta / properties / latency_ms

Added value: +{
+  "description": "Wall-clock milliseconds this tool call took, measured server-side around the handler.",
+  "minimum": 0,
+  "type": "integer"
+}

Changed1 schema field changedJun 18, 2026
- addedOutput schema / properties / _meta / properties / pit_safe / description
```
Added value: +"true iff a zero-look-ahead point-in-time cut was applied to every returned figure"
```
AddedMay 28, 2026

TDQS

A3.5/5.0

Behavior1/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description explicitly claims 'Idempotent — re-calling only re-resolves what changed,' but the annotations declare idempotentHint=false. This is a direct contradiction, so behavioral transparency is scored 1 per the rubric despite otherwise useful scope and return disclosures.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Four sentences, front-loaded with the core action and eligibility criteria, and every sentence carries operational value. The customer_id guidance partially duplicates the schema's own parameter description, preventing a perfect conciseness score.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With an output schema present, return-value detail is not required; the description still provides summary/per-claim expectations, scope, eligibility, restrictions, and idempotency. The conflicting idempotency signal is the only meaningful completeness gap.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all three parameters. The description reinforces the customer_id restriction and 'omit customer_id' guidance, but adds no new meaning for max or as_of beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a precise verb and resource: find every auto-gradable claim that is due and resolve it against fundamentals. It defines eligibility (open/needs_review/stale or passed horizon) and the 'bulk' scope, clearly distinguishing it from single-claim or thesis scoring tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives clear context: use it to bulk-score the caller's own due claims, with an explicit exclusion that targeting another user's customer_id is rejected on every plan. It does not name sibling alternatives like score_claim or score_due_theses, so sibling boundaries are implied rather than explicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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