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ateam-mcp

by ariekogan
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Hybrid

ateam_verify_consistency

Detects drifts between Builder filesystem and GitHub for a solution, listing files that differ or are missing on either side. Run after GitHub patches to confirm consistency before building.

Instructions

Check that the Builder filesystem state and GitHub state are in sync for a solution. Read-only probe — does NOT trigger a deploy.

Returns: • ok: true + drifts: [] if everything matches • ok: false + drifts: [{path, kind}] listing files that differ (kinds: fs_missing, gh_missing, content_differs)

Drift can creep in when GitHub writes happen but Builder FS doesn't get the mirror update (network blip, container restart mid-write). Boot sync heals most of it on next backend restart; this tool surfaces drift earlier.

Run after a series of ateam_github_patch calls to confirm the Builder backend is consistent with GitHub before you ateam_build_and_run.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
solution_idYesThe solution ID to verify

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.52

TDQS

A4.7/5.0
Behavior5/5

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

Even though no annotations are present, the description fully discloses read-only behavior ('does NOT trigger a deploy'), defines exact return structure (ok, drifts with kinds), and explains drift cause. This is strong behavioral transparency for a no-annotation tool.

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?

Description is well-structured with a leading one-sentence summary, bulleted return format, and a short implementation note. All sections earn their place; there is no fluff or redundancy.

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?

No output schema is provided, so the description compensates by detailing both success and failure return values including drift kinds. It also provides use-case context and sibling sequencing, making it fully self-contained for a tool of this complexity.

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?

Only one parameter, solution_id, is already fully described in the schema as 'The solution ID to verify' (100% coverage). The description adds no further parameter semantics beyond using the phrase 'for a solution', so baseline 3 is appropriate.

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?

Description uses specific verb 'Check that ... are in sync' and identifies the exact resource (Builder filesystem state vs GitHub state). The phrase 'Read-only probe — does NOT trigger a deploy' clarifies its non-mutating nature, distinguishing it from deploy/update tools like ateam_redeploy or ateam_github_patch.

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?

Explicitly instructs to 'Run after a series of ateam_github_patch calls' and before 'ateam_build_and_run', providing clear temporal context. It also contrasts with boot-sync healing, implying when early verification is valuable and when it is unnecessary.

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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