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Robots Policy Lint

Diff two robots.txt by effect

diff_robots_txt
Read-onlyIdempotent

Compare two versions of a robots.txt and report only the crawlers whose verdict actually changes at a given path — not the text difference. Answers 'did my edit do what I meant, and did it do anything else', including sitemap additions and whether the parse errors went up or down.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathNoPath to compare verdicts at. Defaults to "/".
afterYesThe new robots.txt.
beforeYesThe old robots.txt.

TDQS

A4.4/5.0
Behavior5/5

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

Beyond the readOnlyHint and idempotentHint annotations, the description discloses non-obvious behavioral details: it filters to verdict changes, includes sitemap additions, and tracks whether parse errors went up or down. This goes well beyond what annotations provide and helps the agent anticipate the tool's output style.

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 sentences, with the core behavior front-loaded and no redundant wording. The motivating question is answered efficiently without repeating schema data or annotation values.

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?

The description explains what the tool returns: changed crawler verdicts, sitemap additions, and parse-error trends, which is important because no output schema is provided. It stops short of describing the exact response structure, but an agent has enough context to invoke the tool 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 before, after, and path are already documented in the input schema. The description adds no parameter-specific detail, but none is needed because the schema carries the full burden; baseline 3 applies.

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 a specific action: compare two robots.txt versions and report only crawlers whose verdict changes at a given path. It explicitly distinguishes itself from a text diff, making the tool's purpose unambiguous even without inspecting the schema.

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

Usage Guidelines4/5

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

The description frames the intended use case: checking whether a robots.txt edit did what was meant and did not cause unintended changes. It does not explicitly name sibling alternatives or state when not to use it, but the context is clear enough for an agent to choose it appropriately.

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

A4.5/5.0
Disambiguation5/5

Each tool has a distinct job: linting syntax, auditing AI crawler access, checking a specific path, diffing two versions, and merging a policy stance. Although audit_ai_access and check_path_allowed both evaluate robots.txt access, one is crawler-level across the whole file and the other is path-level for a single crawler, so they are not easily confused.

Naming Consistency5/5

All tool names follow a consistent snake_case verb_noun pattern: audit_, check_, diff_, lint_, merge_. The objects are clear and the verbs accurately signal the operation, so the naming scheme is predictable and uniform.

Tool Count5/5

Five tools is a well-scoped size for a robots.txt linting and policy analysis server. Each tool covers a meaningful operation without redundancy, and the count feels neither thin nor bloated.

Completeness5/5

The tool set covers the core lifecycle of robots.txt analysis: linting for errors, auditing AI access, evaluating specific paths, diffing version changes, and merging maintained policy stances. No obvious dead ends or missing operations exist for the stated domain.

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