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Repository Insights

get_repo_insights
Read-onlyIdempotent

Get repository insights: stars, forks, traffic (clones/views), referrers, and popular paths. Use "sections" to control token usage: stars (~50 tokens), traffic (~100), referrers (~100), paths (~100), or all (~350).

Instructions

Get repository insights: stars, forks, traffic (clones/views), referrers, and popular paths. Use "sections" to control token usage: stars (~50 tokens), traffic (~100), referrers (~100), paths (~100), or all (~350).

Input Schema

NameRequiredDescriptionDefault
repoNoRepository name - LEAVE EMPTY to auto-detect
ownerNoRepository owner - LEAVE EMPTY to auto-detect
sectionsNoData section to return (default: stars). Use "all" for full payload.
use_test_dbNo

Output Schema

NameRequiredDescriptionDefault
codeNoError code (e.g. VALIDATION_ERROR, INTERNAL_ERROR)
repoNo
sizeNo
errorNoHuman-readable error message
forksNo
ownerNo
pathsNo
starsNo
detailsNoAdditional error context
sectionNo
successNo
trafficNo
categoryNoError category (validation, query, connection, internal)
watchersNo
referrersNo
openIssuesNo
suggestionNoSuggested fix for the error
instructionNo
recoverableNoWhether the error is recoverable
defaultBranchNo
aggregated_errorsNoDetails of individual errors in a multi-step operation
requiresUserInputNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv9.0.0

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so the safety profile is covered. The description adds genuinely non-obvious behavioral context the annotations cannot convey: the per-section token cost (~50 to ~350 tokens). It omits the notable behavioral caveat that traffic/referrer/path data is only available with push access on GitHub.

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 tight sentences: the first states what data is available, the second gives the token-cost decision rule. Zero filler and the scoping mechanism is front-loaded.

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?

An output schema exists, so return-value explanation is rightly omitted, and the token-cost guidance is the key missing piece an agent needs. Minor gaps remain: "forks" is advertised in the description but is not a selectable section value in the enum, and the repo/owner auto-detect behavior is only in the schema.

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

Parameters4/5

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

Schema coverage is 75% and already documents repo, owner and sections with defaults. The description adds value beyond the schema by quantifying the token cost of each section value, letting the agent pick sections rationally. The undescribed use_test_db parameter and the schema's minimal enum description are not compensated for, keeping it below 5.

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 gives a specific verb+resource ("Get repository insights") and enumerates exactly which data categories are returned: stars, forks, traffic (clones/views), referrers, and popular paths. An agent can immediately tell this is a GitHub repo analytics reader. It stops short of naming a sibling it might be confused with (e.g. get_statistics or get_cross_project_insights in the sibling list), so no explicit differentiation is made.

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 clear operational context: "Use 'sections' to control token usage" with per-section token budgets, which tells the agent how to call it efficiently. However, there is no when-to-use/when-not guidance relative to alternatives, and no mention that traffic/referrers/paths data typically requires elevated repo permissions.

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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