Gluecron

gluecron_repo_search

Read-only

Search Gluecron repositories by keyword (name + description), case-insensitively. Returns public repos plus any private repos owned by the authenticated caller. Default 20 per page, max 50; total is the full match count and nextOffset pages through it.

Input Schema

TableJSON Schema

Name	Required	Description
`limit`	No	Max rows per page (default 20, max 50)
`query`	Yes	Search keyword (1-100 chars)
`offset`	No	Rows to skip. Use `nextOffset` from the previous response.

TDQS

A3.9/5.0

Behavior5/5

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

Beyond the readOnly and non-destructive annotations, the description discloses case-insensitive matching, searchable fields, authentication ownership scope, and the full pagination contract (default/max per page, total count, nextOffset). This gives the agent a clear behavioral model with no contradictions.

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 front-load the core action and then provide essential pagination detail. There is no filler, repetition, or unnecessary elaboration.

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?

With no output schema, the description still explains what is returned, ownership visibility, and how pagination works. It would be fully complete if it named the fields of each returned repository item and explicitly addressed the sibling search_repos ambiguity.

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 100%, so the baseline is 3. The description adds value by explaining how offset relates to nextOffset and that total is the full match count, giving operational meaning to the pagination parameters beyond their schema descriptions.

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 clearly identifies the action: searching Gluecron repositories by keyword in name and description, with case-insensitive matching. It is specific about scope and distinguishes the tool's behavior, but it does not explicitly differentiate itself from the similarly named sibling gluecron_search_repos.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No when-to-use or alternative guidance is provided, especially relative to the near-duplicate sibling gluecron_search_repos. The scope detail about public/private repos is contextual, but it does not tell an agent when to choose this tool over other search 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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TDQS

B3.4/5.0

Disambiguation2/5

Several tools have near-identical purposes, such as `gluecron_read_file` and `gluecron_repo_read_file` (both read a file from a repo), and `gluecron_explain_repo` and `gluecron_repo_explain_codebase` (both return cached AI explanation). This creates ambiguity despite minor differences in description. While many tools are distinct, the overlapping pairs force an agent to choose between effectively equivalent operations, lowering disambiguation.

Naming Consistency4/5

All tools use the `gluecron_` prefix followed by a verb_noun pattern (e.g., `acquire_lease`, `create_issue`, `merge_pr`). A few tools like `gluecron_ai_cost_summary` and `gluecron_repo_explain_codebase` deviate slightly but remain readable and predictable. Overall, the naming convention is largely consistent, making it easy to infer tool function from the name.

Tool Count2/5

With 60 tools, the server far exceeds the 25-tool threshold for 'too many' per the guidelines. Although the server covers a broad developer platform (repository management, issues, PRs, workflows, AI features, etc.), the sheer number of tools makes navigation heavy and risks overwhelming both agents and users. A more focused set would improve coherence.

Completeness5/5

The tool set is remarkably thorough, covering nearly every lifecycle stage for repositories, issues, pull requests, workflows, branches, commits, and AI-assisted features (chat, test generation, release notes, refactoring, voice-to-PR). Essential CRUD operations are present, and advanced operations like leasing, sandbox provisioning, and multi-repo refactoring are included. There are no obvious gaps for the stated purpose of a developer platform.

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