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Glama

faf_check

Inspects human_context fields and rates each as empty, generic, or good to gauge context quality. Optionally protects good fields or clears that list.

Instructions

Inspect the human_context fields and rate each empty/generic/good. Returns the ratings; with protect it records the good fields in _protected_fields as an advisory list (other tools do not enforce it), with unlock it clears that list. Use this to gauge context quality.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathNoProject path. Sets session context for subsequent calls.
unlockNoClear the _protected_fields list
protectNoRecord good fields in _protected_fields (advisory; other tools do not enforce it)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv2.3.2
    • changedInput schema / properties / protect / description
      Previous value: -"Lock good/excellent fields from being overwritten"New value: +"Record good fields in _protected_fields (advisory; other tools do not enforce it)"
    • changedInput schema / properties / unlock / description
      Previous value: -"Remove all field protections"New value: +"Clear the _protected_fields list"
  2. First observedv2.1.1

TDQS

A3.7/5.0
Behavior4/5

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

Annotations only give the generic readOnlyHint=false/destructiveHint=false profile, while the description adds the genuinely useful disclosure that _protected_fields is advisory and NOT enforced by other tools, plus that unlock clears the list. That is real behavioral context beyond structured fields. It stops short of stating persistence or the shape of the returned ratings.

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?

Three sentences, front-loaded with the core operation and no filler; the protect/unlock clauses are appended efficiently. The semicolon-chained middle sentence is slightly dense but nothing is wasted.

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 no output schema and only three simple parameters, the description covers the operation, the two mutating flags, and the advisory caveat. An agent has enough to call it correctly; only return-format details are absent, which is a minor gap for a tool that returns ratings.

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 all three parameters (path, protect, unlock) are already documented in the schema, and the description's explanation of protect/unlock largely restates the schema wording. Baseline 3 is appropriate since the schema does the heavy lifting.

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

Purpose4/5

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

The description names a specific verb (inspect), a specific resource (human_context fields), and the operation performed (rate each empty/generic/good). It is clear what the tool does, though it never contrasts itself with the adjacent faf_score or faf_context siblings, so an agent must infer the boundary.

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?

"Use this to gauge context quality" implies the intent but gives no when-to-use vs. when-not guidance and never names an alternative (e.g. faf_score). The protect/unlock conditions are described, but that is parameter behavior rather than tool-selection guidance.

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