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Glama

memory_lint

Scan markdown, JSON, or JSONL memory stores to find exact duplicates, contradictions, and stale entries, returning each finding with its fidelity band.

Instructions

Lint a memory store (markdown / JSON / JSONL) for exact duplicates, contradictions and staleness. Returns the scanner's findings; each one carries the fidelity band of the claim it came from.

Input Schema

NameRequiredDescriptionDefault
storeYespath to the memory store file
engineNodetection engine; 'embed' needs a local Ollama (default: heuristic)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.0

TDQS

A3.6/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. 'Lint' conventionally implies a non-mutating scan, but the description never explicitly confirms the store is not modified, nor does it mention permissions, cost, or that the embed engine requires a local Ollama (that detail lives only in the schema). It does add useful disclosure about the shape of findings via the fidelity band.

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 tightly written sentences with zero filler: the operation and its formats lead, the checks follow, and the return characterization closes. Every clause earns its place.

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?

For a two-parameter read-only scanner with no output schema, the description covers the resource, formats, checks, and the structure of returned findings. The main omissions — explicit confirmation of non-mutation and engine prerequisites — are minor.

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%, and both parameters (store path, engine enum with its Ollama caveat) are documented there, so the baseline is 3. The description's mention of accepted store formats adds a small amount of context for the 'store' path but no syntax or format details beyond the schema.

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?

States a specific verb (lint) and resource (memory store), plus the accepted formats (markdown/JSON/JSONL) and the three checks performed (duplicates, contradictions, staleness). It does not explicitly differentiate itself from the sibling memory_admit, but the verb makes the distinction inferable.

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?

Usage is implied — run it to audit a store for duplicates, contradictions and staleness — but there is no explicit when/when-not guidance and the sibling memory_admit is never referenced. Nothing tells the agent whether linting should precede or follow admission.

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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