Skip to main content
Glama

vigile_recall

Recall prior security memory for an entity, pattern, or incident, returning compact context with evidence chunks and source references.

Instructions

Recall prior Vigile security memory context for an entity, pattern, or incident. Returns compact context, evidence chunks, and source references with provenance status.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesRecall query, e.g. 'previous incident for inc_123'
scopeNoOptional retrieval scope filters
max_chunksNoMaximum evidence chunks (default: 8)
risk_levelNoSet to high for high-risk actions
retrieval_modeNoExperimental retrieval mode
Behavior2/5

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

With no annotations provided, the description bears full responsibility for behavioral traits. It mentions return types but does not disclose whether the tool is read-only, idempotent, requires specific permissions, or has any side effects. This is insufficient for a tool that lacks annotation support.

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?

The description is two sentences, front-loaded with the main action and followed by return details. Every sentence adds necessary information with no redundancy or filler.

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

Completeness3/5

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

Given the tool has 5 parameters, no output schema, and no annotations, the description provides a high-level overview of returns but lacks details on output structure, error handling, or behavioral constraints. It is adequate but not complete for safe agent usage.

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 the schema already documents all parameters. The description adds no extra meaning beyond the schema, such as examples, dependencies, or formatting constraints. The baseline of 3 is appropriate given high coverage.

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 it recalls prior Vigile security memory context and specifies what is returned (compact context, evidence chunks, source references with provenance status). It effectively distinguishes from siblings like vigile_remember (store) or vigile_check_provenance (verify) by focusing on retrieval of past data.

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 description implies usage for recalling prior context but provides no explicit guidance on when to use this tool versus alternatives like vigile_search or vigile_timeline. It lacks instructions on when not to use it, leaving the agent to infer from context.

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/Vigile-ai/vigile-mcp'

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