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ateam-mcp

by io.github.ariekogan

ateam_chain_status

SLIM chain status — the chip-quick poll. Given a chain_id (from ateam_conversation), returns the WHOLE-CHAIN aggregate status cheaply: chain_status + chain_done (true only when the ENTIRE chain — root job + every handoff + askAnySkill subcall — is terminal), plus pending_question, result, and a short progress line.

This is what you poll on a loop after ateam_conversation — NOT ateam_get_chain (that returns the full tree; too heavy for periodic polling). A single job can finish while the chain is still running, so poll chain_done, not a job's status.

Loop: call every ~2s until chain_done === true (or pending_question is set — the assistant is waiting on the user). Then read result / fetch the full tree once via ateam_get_chain if you need per-job detail.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
job_idNoAlias for chain_id — any job in the chain resolves to the chain aggregate. The handler has always accepted it; without this declaration MCP stripped it before the handler could see it.
actor_idNoOptional. WHO is asking. A job belongs to an actor and Core enforces that on per-job reads, so a tenant key alone is refused. Usually unnecessary — the session remembers the actor from ateam_conversation/ateam_test_skill. Pass it to inspect a job run by a DIFFERENT actor (e.g. a real user's).
chain_idYesThe chain id returned by ateam_conversation (the conversation's identity). Any job id in the chain also works — Core resolves the chain aggregate.

TDQS

A4.7/5.0
Behavior5/5

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

There are no annotations, so the description carries the full behavioral disclosure burden. It does so well: it discloses cost/performance traits ('chip-quick', 'cheaply'), explains the precise semantics of chain_done, and warns that an individual job can finish while the chain is still running. This prevents a common polling mistake.

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 longer than minimal, but every sentence earns its place by enabling correct loop behavior. The key differentiator ('NOT ateam_get_chain') is front-loaded, and the ending gives a clear actionable sequence.

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?

Since there is no output schema, the description must explain return semantics in prose, and it does: chain_status, chain_done, pending_question, result, and a progress line. It also covers the full interaction lifecycle, from initial poll through termination and optional fallback to ateam_get_chain for detailed per-job data.

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 tool description reinforces that chain_id comes from ateam_conversation and that job_id aliases to the chain aggregate, but the schema already documents these relationships. There is no substantial new parameter meaning added in the description.

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 identifies the tool as a lightweight whole-chain status poll, naming the exact resource (chain_id from ateam_conversation) and the fields returned. It explicitly distinguishes itself from ateam_get_chain, so an agent can select it correctly without inspecting the sibling.

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 explicitly says when to use this tool ('poll on a loop after ateam_conversation') and when not to ('NOT ateam_get_chain'). It also gives a concrete polling recipe: call every ~2 seconds until chain_done or pending_question is set, then optionally fetch the full tree via ateam_get_chain.

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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