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

With no annotations, the description carries the full burden and uses it well: it reveals that an LLM drafts the spec, that it runs in a real browser (implying actual page interaction), and that API keys are required. It also states the output artifacts. It doesn't mention potential side effects on the target URL, but the 'real browser' clause provides transparency.

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

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

Four sentences, each with a distinct role: core action, user input guidance, prerequisite, and return values. No redundancy or extraneous details; the most important information is front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description adequately bridges the gap by enumerating the return values: spec path, PASS/FAIL verdict, per-step results, and report path. It also covers prerequisites and usage context, making it complete for the tool's moderate complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3. The description goes beyond by providing an example for the 'requirements' parameter ('dark-mode toggle changes the background color') and tying the 'out' parameter to both spec and report paths, which adds meaning not fully spelled out in the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with 'AI-drafts an acceptance checklist... then immediately runs it in real Chromium', which specifies the verbs (drafts and runs) and resource (acceptance checklist for a URL). This clearly distinguishes it from siblings like verify_spec and verify_url by highlighting the generation step before verification.

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

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

It gives explicit context for use: pass requirements in plain language as QA criteria, and it notes the prerequisite of DEEPSEEK_API_KEY or OPENAI_API_KEY. However, it does not explicitly state when to use this tool instead of verify_spec or verify_url, so it earns a 4 rather than a 5.

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

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

No annotations are provided, so the description carries the full burden. While it states the purpose, it does not disclose whether the check is read-only, what the result looks like, or what happens if components are not ready. For a health check, this is a notable gap.

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

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

A single, front-loaded sentence that is concise and free of filler. It communicates the essential purpose without wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple 0-parameter tool, the description covers the main purpose but omits the expected response or how to interpret the check result. Since there is no output schema, adding a brief note about the return value would make it more complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

There are zero parameters, so schema coverage is complete. No parameter documentation is needed, and the baseline of 4 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool checks the readiness of the dsh-verify MCP server and its Chromium browser. The verb 'check' and the specific resource distinguish it from sibling tools that actually run verifications.

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

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

The description implies this is a pre-flight check before running verifications ('ready to run verifications'), but it does not explicitly state when to use this tool versus the verification siblings, nor does it provide exclusions.

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

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

With no annotations provided, the description carries the burden of behavioral disclosure. It explains that the tool is deterministic ('no LLM judges the outcome'), returns PASS/FAIL with per-step results and an HTML report, and defines exit-code semantics. It does not mention side effects like output directory creation or browser dependency, but these are partially inferable from the schema and tool nature.

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

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

The description is four concise sentences with no fluff or repetition. It front-loads the core action and packs essential nuance about targets, outputs, and determinism into a compact space.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has no output schema, but the description explicitly covers return values (PASS/FAIL with per-step results and HTML report) and exit-code semantics. All four parameters are documented in the schema, and the description adds behavior context. There are no significant gaps for an agent to invoke the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the parameters are well-documented in the schema. The description adds modest context by explaining spec structure (spec.serve, spec.base/step.url) and that specPath can be a glob, but it does not materially enhance parameter semantics beyond what the schema already provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Run a dsh-verify acceptance spec (JSON file, or glob) against a real headless Chromium.' This is a specific verb+resource pairing. It also distinguishes itself from siblings like verify_url by focusing on acceptance specs rather than single URLs, and from generate_and_verify by not mentioning any generation step.

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

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

The description gives useful context on when to use the tool, such as the ability to serve a local static dir or target any URL, implying it is for spec-driven verification. However, it does not explicitly state when to use an alternative like verify_url for simple URL checks, so it lacks direct when-not guidance.

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

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

With no annotations provided, the description fully discloses key behaviors: it uses a real headless Chromium, lists all supported check steps, automatically prepends goto if missing, returns PASS/FAIL with per-step results and an HTML report, and emphasizes deterministic execution (no LLM judging). This goes far beyond a simple 'verify' statement.

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

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

The description is three sentences long and extremely information-dense. It front-loads the core purpose and packs the check action list and output semantics into a compact, readable format with no irrelevant details.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

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 clearly explains what the tool returns (PASS/FAIL, per-step results, HTML report path) and how it operates. It could mention potential side effects of click/fill actions or network dependencies, but the given detail is strong for a verification tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema describes all four parameters with 100% coverage, so the baseline is 3. The description adds operational context for the checks parameter (list of actions, prepending goto) and clarifies output behavior, but does not significantly augment the schema beyond that.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Verify') and resource ('a live URL') and elaborates on the method with a detailed list of check actions. It clearly distinguishes itself from siblings (health, verify_spec, generate_and_verify) by focusing on human-style browser-based verification of a live URL.

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

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

The description clearly implies when to use this tool: when you need to run human-style browser checks against a live URL. It does not explicitly mention alternatives or exclusions, but the context is unambiguous and sufficient for tool selection.

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