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coderegistry

by io.github.hellosg

get-contributors

Returns aggregated contributor stats (commit count, lines added/deleted, first/last commit) for a project (all vaults) or a single vault. Provide exactly one of project_id or vault_id. Requires full data access (a paid plan; verification-only plans are not included). Requires X-API-Key (existing users can generate an API key in the web app). If headers aren't supported, pass api_key in arguments.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax results to return (default 50, max 200).
authorNoFilter: exact match on commit author (case-insensitive).
branchNoFilter: exact match on branch name.
offsetNoNumber of results to skip, for pagination.
api_keyNoOptional API key for clients that cannot set X-API-Key headers.
date_toNoFilter: commits on or before this date (YYYY-MM-DD).
vault_idNoVault id (from create-code-vault or list_vaults). Returns data for this vault only.
date_fromNoFilter: commits on or after this date (YYYY-MM-DD).
project_idNoProject id (from create_project). Returns data aggregated across all vaults in the project.

TDQS

A4/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It adds valuable auth/plan requirements and the header-fallback behavior. However, it doesn't describe error behavior, pagination semantics, or the full response structure beyond listing a few stat names, leaving some behavioral transparency gaps.

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?

Three sentences with no filler. The first sentence front-loads the purpose and scope, the second states the key constraint, and the third covers auth. Every sentence earns its place.

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 stats endpoint, the description covers purpose, scope, authentication, and output content. It doesn't mention error cases or response format in detail, but the output fields are named and the schema descriptions cover all parameters, so the tool is callable without missing critical context.

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 the baseline is 3. The description repeats the 'exactly one' constraint and the api_key fallback, both already encoded in the schema. It adds no meaningful parameter detail beyond what the schema already 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?

States a specific verb and resource: 'Returns aggregated contributor stats (commit count, lines added/deleted, first/last commit)'. Clearly identifies scope ('for a project (all vaults) or a single vault'), which differentiates it from sibling tools like get-git-history or get-components.

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?

Provides clear context: exactly one of project_id or vault_id, full data access required, X-API-Key required, and an api_key fallback for clients without header support. It doesn't explicitly name alternative tools or when-not-to-use conditions, but the context is sufficient for correct routing.

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

A3.7/5.0
Disambiguation3/5

Tools are mostly distinct by resource and action, but the three get-code-vault-* variants (summary, results, reports) plus get_vault create a cluster of similar-sounding retrieval tools. The use of both 'vault' and 'code-vault' in names increases the chance of misselection, though descriptions do clarify the differences.

Naming Consistency2/5

Naming convention is inconsistent: snake_case (create_account, get_vault, list_projects) is mixed with kebab-case (create-code-vault, get-code-vault-summary, reanalyze-code-vault). The same concept is referred to as 'vault' and 'code-vault' across tool names, breaking predictability.

Tool Count4/5

At 16 tools, the server is slightly over the ideal 3-15 range but still reasonable for the domain covering accounts, projects, vaults, and analysis retrieval. The count is justified by the distinct resources and operations, though a few vault-related tools could potentially be consolidated.

Completeness4/5

The server provides solid lifecycle coverage: account create/get/delete, project CRUD (minus update), vault create/read/delete/reanalyze, plus API key rotation. Minor gaps exist, such as no update methods for accounts or projects, but the core workflows are well-supported without dead ends.

Resources