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cognitivemyriad

Verified Repo Memory

vrm_store

Save repository-scoped facts with file citations, automatically extracting snippets to prevent stale information for AI coding agents.

Instructions

Store a memory with file citations. Snippets are auto-extracted.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
factYes
tagsNo
reasonNo
subjectYes
ttlDaysNo
citationsYes
Behavior2/5

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

With no annotations, the description must disclose all behavioral traits. It adds one useful detail (snippets are auto-extracted) but does not mention permissions, irreversibility, TTL behavior, conflict handling, or what the function returns. For a mutation tool with 6 parameters, this is insufficient.

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 short sentences, front-loaded with the action and key feature. No wasted words; every word earns its place.

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?

The tool has 6 parameters, no annotations, and no output schema, yet the description provides almost no context about what a memory is, how citations work, what snippet extraction means, or what the caller should expect. This level of sparsity is inadequate for an agent to invoke the tool intelligently.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate for parameter meanings. It only vaguely references 'file citations' but does not explain subject, fact, tags, reason, or ttlDays. The raw schema provides types and constraints but no semantic guidance, leaving a significant gap.

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?

The description clearly states the action (store), the resource (a memory), and the key differentiator (file citations with auto-extracted snippets). It stands apart from sibling tools like vrm_search and vrm_list which are read operations, and vrm_forget which is a delete operation.

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?

The verb 'store' and the context of sibling tools imply that this is the write operation vs. read/search operations, but the description does not explicitly state when to use this tool or when to prefer alternatives. There are no exclusions or prerequisites mentioned.

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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