Valuein — SEC EDGAR Fundamentals & Smart-Money Data

Test Rule (dry run)

test_rule

Read-onlyIdempotent

Dry-run a rule's condition_expr against a SYNTHETIC trigger payload — reports whether it WOULD have fired, but NEVER dispatches the action (no report generated, no team run, no message sent, no inbox write). Use this immediately after create_rule to sanity-check the condition before it starts evaluating against real events. Pass sample_payload_override to test against specific field values (e.g. {price_change_pct: 12}).

Input Schema

TableJSON Schema

Name	Required	Description	Default
`rule_id`	Yes	Identifier of the rule to dry-run, from create_rule or list_rules.
`sample_payload_override`	No	Merged over the built-in synthetic payload for this rule's trigger_type — lets you test a specific value.

Output Schema

TableJSON Schema

Name	Required	Description
`note`	Yes
`_meta`	Yes	Provenance envelope — data lineage for every MCP response
`reason`	Yes
`rule_id`	Yes
`would_fire`	Yes
`action_type`	Yes
`synthetic_payload`	Yes

Schema Changelog

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

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"
+}

AddedJul 3, 2026

TDQS

A5/5.0

Behavior5/5

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

Description details behavioral traits beyond annotations: 'no report generated, no team run, no message sent, no inbox write'. This complements the readOnlyHint and idempotentHint annotations with concrete side-effect guarantees. No contradiction with 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 sentences, each earning its place: purpose, usage context, parameter guidance. Front-loaded with key action and constraint. No wasted words.

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?

Tool complexity is low (2 parameters, 1 required), but description covers purpose, usage, parameter semantics, and behavioral transparency. Output schema exists, so return value explanation is unnecessary. Complete for effective agent invocation.

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

Parameters5/5

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

Schema coverage is 100%, but description adds significant meaning: explains sample_payload_override is 'Merged over the built-in synthetic payload for this rule's trigger_type — lets you test a specific value.' This clarifies behavior beyond the schema's description. Provides usage context for both parameters.

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 'Dry-run a rule's condition_expr against a SYNTHETIC trigger payload — reports whether it WOULD have fired, but NEVER dispatches the action'. The verb (dry-run), resource (rule), and scope (condition test) are explicit. No sibling tool named test_rule, so no ambiguity.

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 recommends use 'immediately after create_rule to sanity-check the condition before it starts evaluating against real events.' It also clarifies what the tool does NOT do (no action dispatch), providing clear when-to and when-not-to guidance.

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

All Valuein — SEC EDGAR Fundamentals & Smart-Money Data tools Inspect

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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.

Test Rule (dry run)

Input Schema

Output Schema

Schema Changelog

TDQS

Glama MCP Gateway

TDQS

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