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anvai-labs

anvaiops-mcp

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by anvai-labs

memory_search

Search past incidents, fixes, runbooks, and decisions with source, team, and resolution details. Use before investigating production issues or repeating work.

Instructions

Search operational memory: past incidents, fixes, runbooks, and decisions with provenance (source, team, resolution time, RCA and fix summaries). Use before investigating any production issue or repeating work — the answer may already exist.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNoLookback window in days (default 365)
teamNoOwning team, e.g. Platform Engineering
limitNoMax results, 1-50 (default 10)
queryYesNatural-language search query.
statusNoopen | resolved | closed
sourcesNoComma-separated source filter: jira,slack,zendesk,confluence,pagerduty,github
severityNocritical | high | medium | low
componentNoAffected component substring

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations and no output schema, the description carries the full burden, and it usefully discloses the shape of what comes back — source, team, resolution time, RCA and fix summaries. It does not state read-only/non-destructive safety, rate limits, or pagination behavior, which is the remaining gap for an unannotated tool.

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 sentences, no padding: purpose with scope first, then the usage imperative. Every clause earns its place and nothing is buried.

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 an eight-parameter tool with full schema coverage and no output schema, the description compensates well by describing the provenance fields returned. Only the absence of safety/pagination context keeps it from being fully complete.

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 all eight filters (days, team, limit, status, sources, severity, component) are already documented in the schema. The description adds no syntax, format, or interaction detail beyond that, so the baseline 3 applies.

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?

States a specific verb+resource ("Search operational memory") and enumerates the resource contents (incidents, fixes, runbooks, decisions with provenance). This is clearly a read/search tool that an agent can distinguish from the memory_write and memory_status siblings without inspecting either schema.

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

Usage Guidelines4/5

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

"Use before investigating any production issue or repeating work — the answer may already exist" gives a clear triggering condition and the rationale behind it. It lacks explicit exclusions or a named alternative tool to use when the answer is not found, so it stops short of a 5.

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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