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Explain the limits of a result

explain_limits

Returns what a category's (or run's) result can and cannot tell you: status and its meaning, fixture flag, freshness, expiry, explicit limits, conflicts, funding, published errata (each chained to the served result hash), the legal preflight verdict per tool including tools not run, and the answer rule every consumer must follow.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
run_idNoRun id (alternative to category)
categoryNoCategory id

Schema Changelog

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

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It reveals substantial behavior: status meaning, fixture flag, freshness, expiry, explicit limits, conflicts, funding, errata chained to the served result hash, legal preflight verdicts for all tools, and a mandatory answer rule. It does not explicitly say the tool is read-only, but 'Returns' and the content list make the tool's behavior largely transparent.

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?

The description is one dense, front-loaded sentence that begins with the core purpose and then packs in many specific output components. Every listed item adds information, though the long comma-heavy list is harder to scan than a structured or shorter version would be.

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

Completeness3/5

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

The description thoroughly inventories the return content, but it leaves invocation semantics ambiguous: both parameters are optional in the schema and the description does not state whether one is required or what happens if both or neither are supplied. Since there is no output schema, the lack of any return-shape guidance also reduces completeness.

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?

The input schema describes both parameters with 100% coverage, so the baseline is 3. The description adds only the category-vs-run framing, which is largely mirrored by the schema's 'alternative to category' note. It does not add meaningful semantics beyond what the schema already provides.

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?

The description opens with a specific verb and resource: 'Returns what a category's (or run's) result can and cannot tell you' and then enumerates a detailed list of returned aspects. This clearly differentiates it from siblings like get_results, which retrieves raw results, and get_run, which retrieves run details.

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

Usage Guidelines3/5

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

The description implies the tool is for interpreting the limits and meaning of a result rather than retrieving the raw data itself. However, it never explicitly says when to use this tool instead of get_results or get_run, nor does it provide exclusions or alternative routing. Usage context is only implicit.

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

A4.1/5.0
Disambiguation5/5

Each tool has a clearly distinct job: list categories, get category-level results, get run-level bundles, and explain interpretive limits. The overlap in concepts like 'limits' and 'answer rule' is acceptable because explain_limits is explicitly about interpretation while get_results is about the evidence-based answer.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern with simple, specific actions: list, get, get, explain. The naming makes both the action and the resource predictable across the set.

Tool Count5/5

Four tools is a well-scoped size for a read-only evidential querying service. Each tool earns its place and there is no filler or unnecessary duplication.

Completeness4/5

The read/interpretation flow is covered: list categories, fetch category results, fetch run result bundles, and explain limits. The only minor gap is the lack of a direct run-listing endpoint, though list_categories provides source-run pointers and get_run can fetch specific runs.

Resources