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Glama

org_overview

Scan a GitHub org's recent repos to compare CI run counts, failure rates, durations, compute minutes, and zombie crons, identifying which repo's CI to investigate first.

Instructions

Fleet triage across an organization's (or user's) most recently pushed repositories: per-repo run counts, failure rates, median duration, compute minutes, last-run age, and fleet-wide zombie crons (scheduled workflows failing on repeat), one API call per repo. Useful for finding which repository's CI to look at first.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
orgYesGitHub organization or user login
max_reposNoMax repositories to scan, most recently pushed first (default 20)

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?

No annotations are provided, so the description carries the burden. It discloses a notable behavioral trait, 'one API call per repo', which tells the agent about cost/latency, and defines the fleet-wide 'zombie crons' concept. It does not explicitly state read-only semantics or rate limits, but the triage/overview framing implies no mutation.

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 dense sentences with no filler: the first lists all key outputs, and the second gives the usage rationale. The core action and resource are front-loaded, and every phrase adds information.

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?

Given there is no output schema, the description adequately enumerates the returned aggregate metrics and exposes the per-repo API cost. It does not describe exact response formatting or error/pagination behavior, but for selecting and invoking a 2-parameter overview tool, the essentials are present.

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?

Both parameters already have descriptive schema entries: 'org' is identified as a GitHub organization or user login, and max_repos includes default and bounds. The description adds no parameter-specific meaning beyond reusing the 'most recently pushed' concept from the schema, so the baseline score of 3 is appropriate.

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 opens with a clear function, 'Fleet triage across ... most recently pushed repositories,' and specifies the exact metrics returned (run counts, failure rates, median duration, compute minutes, last-run age, zombie crons). It also gives the decision-oriented outcome, 'finding which repository's CI to look at first,' which distinguishes it from per-repo sibling tools like analyze_repo and run_deep_dive.

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?

The description explicitly frames when to use it: as a triage step to decide which repository's CI to investigate first. It does not explicitly name sibling alternatives or state when not to use it, so it falls short of a 5, but the context is clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.