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Valuein — SEC EDGAR Fundamentals & Smart-Money Data

by io.github.valuein

Get Report Version

get_report_version
Read-onlyIdempotent

Author-only fetch of a specific archived version of one of your reports, by positive-integer version. Returns metadata + the full payload (sections, citations, structured, markdown) — enough to render a diff against the current HEAD in the workspace editor. Use after list_report_versions identifies the version number you want; for the current HEAD use get_report instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
versionYesVersion number to fetch (from list_report_versions).
report_idYesIdentifier of the report whose archived version to fetch, as returned by create_report or list_my_reports.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
_metaYesProvenance envelope — data lineage for every MCP response
payloadYes
versionYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed2 schema fields changed
    • 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"
+}
  2. Changed2 schema fields changed
    • 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"
+}
  3. Changed1 schema field changed
    • 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"
  4. Changed1 schema field changed
    • addedInput schema / properties / report_id / description
      Added value: +"Identifier of the report whose archived version to fetch, as returned by create_report or list_my_reports."
  5. Added

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint. Description adds that it returns full payload for diffing and is author-only, which is helpful context beyond annotations.

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

Conciseness5/5

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

Three front-loaded sentences: purpose, return value and use case, usage guidance. Every sentence adds value with no redundancy.

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

Completeness5/5

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

With output schema present and full parameter descriptions, the description completes the picture by explaining when to use and what it returns, leaving no significant gaps.

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 coverage is 100% with clear parameter descriptions. Description does not add additional meaning beyond what schema provides, so baseline 3 is appropriate.

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?

Description clearly states it fetches an archived version of a report by version number, distinguishing it from get_report (current HEAD) and list_report_versions (to identify version).

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

Usage Guidelines5/5

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

Explicitly instructs to use after list_report_versions and to use get_report for current HEAD, providing clear when-to-use and when-not-to-use guidance.

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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TDQS

A4/5.0
Disambiguation5/5

Each tool has a distinct purpose with detailed descriptions that clarify differences. Overlaps like get_peer_comparables vs screen_universe are well-differentiated by scope (single company vs cross-sectional). Similarly, get_insider_sentiment vs get_smart_money_flow are clearly distinguished by data sources and methodology.

Naming Consistency5/5

All tool names follow a consistent verb_noun snake_case pattern (e.g., create_report, get_financial_ratios, delete_alert). No mixing of conventions or inconsistent verbs.

Tool Count2/5

With 69 tools, the count far exceeds the 25+ threshold for 'too many'. While the domain is broad, the sheer volume likely overwhelms agents and increases selection complexity.

Completeness4/5

The tool set covers a wide range of SEC filings, ratios, smart-money data, alerts, reports, and more. Minor gaps exist (e.g., no options or detailed debt data), but most analyst workflows are supported.

Resources