Skip to main content
Glama

faf_check

Read-only

Inspects human_context fields and assigns empty, generic, good, or excellent quality ratings. Protects high-quality fields from being overwritten.

Instructions

Quality inspection for human_context fields + field protection - Shows empty/generic/good/excellent ratings

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
protectNoLock good/excellent fields from being overwritten
unlockNoRemove all field protections
pathNoProject path. Sets session context for subsequent calls.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeYesreport | protect | unlock
qualityPercentNoShare of fields rated good/excellent (report mode)
goodCountNoFields rated good or excellent
emptyCountNoFields that are empty
protectedNoField names currently protected
protectedNowNoFields newly protected by this call (protect mode)
fieldsNoPer-field quality + protection (report mode)
Behavior1/5

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

The description claims the tool can lock or unlock fields via protect/unlock parameters, which are write operations. However, the annotation declares readOnlyHint=true, indicating a read-only intent. This is a direct contradiction between description and annotation, severely reducing transparency.

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 concise, fitting in one line with key actions (inspection, showing ratings) and field protection. However, it could be more structured by separating purpose and parameters.

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

Completeness2/5

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

Despite having an output schema, the description does not explain the return values or behavior in different scenarios. It also lacks context about prerequisites or side effects. The contradiction with annotations further 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?

All three parameters have descriptions in the input schema (100% coverage), so the description adds little extra meaning beyond summarizing the tool's function. Baseline 3 is appropriate as 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 clearly states the tool's purpose: quality inspection for human_context fields and showing empty/generic/good/excellent ratings. It also mentions field protection, which hints at a unique capability, but does not explicitly differentiate from sibling tools like faf_score that might also inspect quality.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives such as faf_score, faf_status, or other inspection tools. There are no explicit context or exclusion statements.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Wolfe-Jam/claude-faf-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server