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Glama

Get Repo

get_repo
Read-onlyIdempotent

Look up ONE named repository by its owner/repo slug — "facebook/react", "torvalds/linux", "vercel/next.js". Use this whenever the repository is named in the question. Answers how many stars / forks / watchers a repo has, what license and language it uses, its topics, description, open issue count, and when it was last pushed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
repoYesRepository name, e.g. "react". Also accepts the full slug "facebook/react".
ownerNoRepository owner (user or org), e.g. "facebook". May be omitted if `repo` carries the full "owner/repo" slug.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesRepository URL
nameYesRepository name
forksYesNumber of forks
ownerYesRepository owner login
starsYesNumber of stargazers
topicsYesRepository topics/tags
is_forkYesWhether the repository is a fork
licenseYesLicense SPDX ID or name
networkYesNetwork count
size_kbYesRepository size in kilobytes
archivedYesWhether the repository is archived
homepageYesHomepage URL
languageYesPrimary programming language
watchersYesNumber of watchers
full_nameYesFull repository name (owner/repo)
pushed_atYesLast push timestamp
created_atYesRepository creation timestamp
owner_typeYesOwner type (User/Organization)
updated_atYesLast update timestamp
visibilityYesRepository visibility (public/private)
descriptionYesRepository description
open_issuesYesNumber of open issues
subscribersYesNumber of subscribers
default_branchYesDefault branch name

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, openWorld, and non-destructive. The description adds context by specifying the tool handles exactly one repo and enumerates the returned data fields, which is useful beyond annotations.

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 well-structured sentences front-load the core purpose and usage. Every clause adds value: the examples clarify input format, and the listed outputs set expectations.

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

Completeness5/5

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

For a simple lookup tool with a rich output schema and strong annotations, the description covers purpose, input format, usage timing, and expected data. No critical gaps remain.

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%, and the schema already documents that repo accepts full slug and owner may be omitted. The description repeats this information without adding new semantic detail beyond what the schema provides.

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 the tool looks up ONE named repository by its owner/repo slug, with specific examples like 'facebook/react'. It identifies the exact resource and distinguishes from search_repos by emphasizing 'named' vs search.

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 provides an explicit when-to-use: 'Use this whenever the repository is named in the question.' It does not explicitly mention alternatives or when-not-to-use, but the context is clear and adequate.

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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TDQS

A3.8/5.0
Disambiguation4/5

Most tools target distinct purposes (e.g., ask_pipeworx vs. get_repo vs. validate_claim), but there is some overlap between ask_pipeworx and ask_pipeworx_grounded, and between bet_research and polymarket_edges. Overall, an agent can generally distinguish them.

Naming Consistency2/5

Tool names lack a consistent pattern: some are verb_noun (search_repos, get_user), others are noun_verb (entity_profile), and many are compound descriptor phrases (polymarket_arbitrage, scan_dependency). This mixed convention makes the set feel disjointed.

Tool Count2/5

38 tools is excessive for a server named 'Github', especially since many tools (e.g., ai_visibility_check, bet_research) are unrelated to GitHub functionality. The count would be appropriate for a broader 'Pipeworx' server but not for a focused GitHub server.

Completeness2/5

The GitHub-relevant tools are limited to read-only operations (get_repo, list_commits, etc.), lacking essential actions like creating/updating repos, issues, or pull requests. The inclusion of numerous non-GitHub tools does not compensate for these gaps.