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ateam-mcp

by io.github.ariekogan

ateam_spec_search

Semantic search over the FULL ateam platform /spec documentation — the deep fallback behind ateam_design_advisor. Ask a natural-language 'how do I…' question and get the most relevant doc chunks (with their topic + heading), then read the full topic via ateam_get_spec(topic). Use this when the advisor's pointer isn't enough, or for details/examples on anything — including topics outside the curated capability list. Read-only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesNatural-language question, e.g. 'how do I send a proactive daily reminder?' or 'per-user persistence'.
top_kNoHow many chunks to return (default 8, max 25).

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden. It explicitly states 'Read-only' to signal no side effects, and describes the output shape (most relevant doc chunks with topic and heading). It doesn't mention authentication or rate limits, but for a search tool this is adequate.

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?

The description is four sentences, each earning its place: core purpose, behavior, usage guidance, and safety hint. It is front-loaded with the primary function and uses clear, concise language with no filler.

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 two-parameter search tool with full schema coverage and no output schema, the description covers what it does, when to use it, what it returns, how to follow up, and its read-only nature. It is sufficiently complete for an agent to invoke it correctly.

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 reinforces the query's natural-language nature and provides example usage, but top_k's meaning and default/max are already fully covered by the schema, so the description adds minimal extra value.

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 performs semantic search over the full ateam platform /spec documentation, with specific verbs and resource scope. It distinguishes itself from sibling tools by positioning as the deep fallback behind ateam_design_advisor and explicitly mentions returning doc chunks with topic and heading.

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

Usage Guidelines5/5

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

The description gives explicit when-to-use guidance: 'Use this when the advisor's pointer isn't enough, or for details/examples on anything.' It also names the follow-up tool ateam_get_spec, providing an alternative path, and excludes curated-capability-only usage.

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

A3.9/5.0
Disambiguation4/5

Most tools have clearly distinct purposes, with detailed descriptions that differentiate similar functions like chain polling vs. chain inspection. However, there is slight overlap between ateam_design_advisor, ateam_get_spec, and ateam_spec_search, which all serve design guidance, potentially causing confusion if descriptions are not read carefully.

Naming Consistency4/5

The naming mostly follows a consistent verb_noun pattern with the 'ateam_' prefix (e.g., ateam_get_solution, ateam_create_connector, ateam_test_skill). Minor deviations include ateam_patch (missing object) and ateam_redeploy (verb only), but overall the pattern is predictable and clear.

Tool Count3/5

With 47 tools, the count is high and exceeds the typical 15-tool threshold for a well-scoped set. However, the tools cover a broad and complex platform (auth, deployment, testing, GitHub integration, scaffolding), and each tool appears to have a distinct role, making the count borderline acceptable rather than excessive.

Completeness4/5

The tool set covers the full lifecycle of building, deploying, testing, and managing A-Team solutions, including design, GitHub integration, and verification. Minor gaps exist, such as no explicit tool for deleting individual files (though patching can overwrite) and no standalone skill listing, but these are not critical dead ends for an agent.

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