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KirinBoard

by ai.kirinboard
OverviewDiscussionsAdmin

Daily metric history, for trends

metrics_history
Read-onlyIdempotent

The dashboard's daily metric history for a repository, oldest day first, for trends: is CI getting slower or failing more, is the backlog growing, are runners congested more often? Each day carries what the dashboard recorded that day: issues filed and closed and open, CI runs passed and not passed, active agents, delivery counts (in progress, blocked, under an initiative, on the project board with a Status), and runner capacity (time congested out of time measured). Give days (1 to 90, default 14) and, to keep the answer short, sections. Counts only. Read-only, and it never fails: if the history cannot be read, or the dashboard keeps none, it says why.

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": "metrics_history"
  }
}

Input Schema

NameRequiredDescriptionDefault
daysNoHow many days back, today included (default 14, at most 90).
repoNoowner/name. Optional when the token covers one repository.
sectionsNoOnly these sections: issues, ci, agents, delivery, capacity (default all).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior5/5

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

Annotations already declare read-only, idempotent, non-destructive behavior, and the description adds substantial context: oldest day first, counts only, default and maximum day range, and explicit no-failure behavior with an explanation when history is unavailable.

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 purpose, trend use cases, returned metrics, parameter hints, and failure behavior are mostly front-loaded. The metric enumeration is somewhat long but useful for setting expectations.

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 complex metrics tool with no output schema, the description covers the main sections, counts-only nature, ordering, and failure behavior. It does not specify the exact response shape or how each section maps to concrete fields.

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 coverage is 100%, so the schema already defines all three parameters including defaults, ranges, and the section enum. The description reinforces the purpose of days and sections but does not add syntax or meaning 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?

The description states a specific resource, daily metric history for a repository, and explains its ordering and trend-oriented purpose. It does not explicitly distinguish itself from sibling tools such as ci_history or delivery_summary.

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?

It gives a clear when-to-use scenario by framing the tool around trend questions like slower CI, growing backlog, and runner congestion, and it advises using sections to keep answers short. It stops short of naming exclusions or alternative tools.

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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