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context-keeper

context-keeper

by jarmstrong158
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

verify_quality

Scan entries to identify quality issues like legacy schema, thin reasoning, missing tags, and isolated entries, then return them for enrichment via update_entry.

Instructions

Scan entries for quality issues (legacy schema, thin reasoning, missing tags, isolated entries) and return them for enrichment via update_entry.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

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

Input Schema

NameRequiredDescriptionDefault
project_dirNoAbsolute path to another project to verify
min_reason_charsNoBelow this length, flag the entry as thin (default: 80)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.15.0

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations, the description carries full burden for behavioral disclosure. It says 'scan' and 'return them for enrichment' which suggests read-only, but does not explicitly state that it does not modify data or confirm safety. It also does not disclose output format, permissions, or side effects. The description is too vague.

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 a single sentence that efficiently conveys the core action and outcome. It is front-loaded and contains no filler. However, it could benefit from a bit more structure or clarity on return format, but it is not verbose.

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?

With 2 parameters, no output schema, and no annotations, the description should provide more context about what 'return them' means (list of entry IDs? entry objects? how to use with update_entry?). It also does not clarify whether project_dir is optional or defaults to current project, leaving ambiguity. Incomplete for a tool that feeds into a workflow.

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% with inline descriptions for both parameters. The tool description adds no additional meaning beyond what the schema already provides for project_dir and min_reason_chars. Baseline 3 is appropriate since schema already documents parameters well.

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 scans entries for specific quality issues (legacy schema, thin reasoning, missing tags, isolated entries) and returns them for enrichment via update_entry. The verb 'scan' and the listed issue types give a clear purpose, and it distinguishes from siblings like update_entry (modification) and query_entries (general query).

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 implies a workflow (scan then enrich via update_entry) but offers no explicit guidance on when to use verify_quality versus alternatives like query_entries. It does not mention when-not to use or prerequisites. The mention of update_entry is a hint but insufficient.

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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