Skip to main content
Glama
Sign In

Santismm Knowledge — Harness Engineering, Agentic AI & Governance

by com.santismm
OverviewDiscussionsAdmin

Get one claim with its limits and what would refute it

get_claim
Read-onlyIdempotent

Get one claim by id (HE-CLAIM-001) or slug: the statement, what it rests on, its structured sources, and — always present — what it does NOT establish and the observation that would retire it. Use this to cite the corpus honestly, or to check whether a result you have just measured confirms or falsifies a claim it makes.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "id": "<id>"
    },
    "name": "get_claim"
  }
}

Input Schema

NameRequiredDescriptionDefault
idYesClaim id (e.g. 'HE-CLAIM-001') or slug.
localeNoLanguage of the returned body. Default: en.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already cover readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds a genuine behavioral trait beyond those: the 'always present' guarantee that limitation and refuting-observation fields appear in every response, which shapes how an agent should interpret and report results. 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?

Two sentences with zero filler: the first front-loads the action, identifier format, and return contents; the second carries the usage guidance. The em-dash aside is purposeful because it emphasizes the always-present guarantee rather than decoration.

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?

Given an output schema exists (return values documented) and annotations carry the safety profile, the description completes the picture: what the tool returns, how to identify the claim, and when to use it. Nothing an agent needs to correctly select and invoke this tool is missing.

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 both id and locale are already documented in the schema. The description's 'by id (HE-CLAIM-001) or slug' mirrors the schema's own example without adding new meaning, so the baseline 3 applies.

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 specific verb+resource ('Get one claim by id or slug') and enumerates the distinctive return content: statement, grounds, structured sources, what it does NOT establish, and the observation that would retire it. The title and description together differentiate it sharply from list_claims and the other get_* siblings, which return different resources.

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 two concrete when-to-use scenarios: citing the corpus honestly (because the tool surfaces limitations) and checking whether a measured result confirms or falsifies a claim. Clear context, though it does not explicitly name alternatives or state when-not-to-use it.

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

All Santismm Knowledge — Harness Engineering, Agentic AI & Governance toolsInspect
Try in Browser
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources