Server Quality Checklist

Tool Scores

• get_team_rulesA
  4.5/5.0
  Behavior4/5

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

  With no annotations, the description carries the full burden. It correctly implies a read-only operation ('Returns'), and goes further by disclosing an important domain constraint: the config schema is closed and unknown keys are not applied. It could add more about response format or failure modes, but it provides meaningful behavioral context beyond a simple retrieval statement.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness4/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The purpose is front-loaded in the first sentence, and the follow-up sentences provide essential usage and schema warnings. The config-editing caveat is slightly tangential to the tool's direct action, but each sentence earns its place by preventing agent errors, so it is not bloated.

  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 parameterless getter with no output schema, the description covers purpose, timing, and critical config-schema pitfalls. It does not describe the exact return shape, but combined with the rule-structure mention and external schema link, it is largely complete for safe invocation.

  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?

  The input schema has zero parameters, so the schema already provides full coverage (100%). The description adds relevant context about the structure of rules (id, description, severity), which indirectly helps interpret the returned content, though no parameter documentation is needed.

  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 opens with a specific verb and resource: 'Returns this team's code standards.' It clearly distinguishes the tool from the sibling review_changes by framing the call as a pre-writing step rather than a post-review step, so an agent knows exactly what this tool provides.

  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?

  It explicitly instructs when to call the tool ('Call it BEFORE writing code') and explains why, contrasting with learning standards 'from a review.' This gives clear when/when-not context relative to the sibling tool, leaving no ambiguity about the intended trigger.

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

• review_changesA
  4.6/5.0
  Behavior5/5

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

  With no annotations, the description carries full behavioral disclosure and does so in depth: it states the tool is read-only, describes the two-pass architecture, warns that finding texts are model output and not instructions, constrains suggestedCode usage with committable semantics, clarifies questions[] are non-blocking, and documents the verdict.gate artifact.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness4/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is long but every sentence carries operational value; the core action and timing are front-loaded before the nuanced output-handling rules. It is slightly dense and could be restructured with clearer separation of concerns, but no filler exists.

  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?

  Despite having no output schema, the description covers the verdict location, severity thresholds (major/minor/info), iteration limit, handling of suggestedCode, and semantics of questions[]. Given the tool's complexity and the complete absence of annotation and output-schema support, this is a fully self-contained definition.

  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 description does not need to re-explain mode, scope, or team_llm. It adds meaningful contextual constraints around those parameters (e.g., full vs fast maps to judge presence) but does not add material parameter-level semantics beyond the rich schema, matching the baseline for full schema coverage.

  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 opens with a specific verb and resource: 'Checks code changes against THIS team's standards', naming the exact config source and stack preset, and distinguishes the review action from the sibling get_team_rules (which retrieves rules rather than reviewing changes). The two-pass reviewer/judge flow further clarifies what the tool does.

  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?

  It gives explicit trigger conditions: 'Call it BEFORE finishing a task and before git push', and specifies a termination protocol: call again after fixes, stop when no major findings remain, cap at 2 repeats, then report minor/info findings. It also directs how to handle questions[] versus defects, leaving little room for misapplication.

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.