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

Annotations already establish readOnlyHint=true and openWorldHint=false, and the description adds meaningful non-obvious context about the returned result: it computes a score delta and classifies findings into resolved, remaining, and new. With no output schema, this return-shape disclosure carries real weight, though it omits error/edge behavior for mismatched or missing scans.

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 with a colon-delimited enumeration of the diff components. Zero filler, and the core purpose is stated before the detail.

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 low-complexity read-only comparison tool, the description covers purpose and output categories, which is close to sufficient. Gaps remain: no statement of prerequisites (both scans must exist, plausibly from the same project), no behavior when the scans are unrelated or an id is invalid, and no routing guidance against the report/scan siblings.

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 only 33% (only `lang` is documented), so the description must compensate. The before/after framing maps onto `before_id`/`after_id` and confirms ordering semantics (which scan is the baseline), but it adds little beyond what the parameter names already convey and says nothing about id format or same-project requirements.

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?

Clear specific verb+resource ('Compare two scans') plus an enumeration of what the diff contains (score change, resolved, remaining, new). It never distinguishes itself from siblings like slop_report (single-scan report) or slop_scan, so an agent must infer the difference from the name alone.

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?

Usage is implied by the before/after framing — compare an earlier scan with a later one after fixes. However, there is no explicit when-to-use guidance, no stated prerequisite that both scan ids must exist (and presumably belong to the same project), and no routing to alternatives such as slop_report when only one scan is of interest.

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?

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety is covered. The description adds genuinely non-obvious behavior: omitting finding_id selects the most important open finding and lists the others, and the response shape (before/after, done-when check) is disclosed despite there being no output schema.

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?

Two sentences, no filler, and the deliverable is front-loaded before the fallback behavior and usage note. Every clause carries information an agent needs.

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 read-only, single-parameter-required tool with no output schema, the description covers the deliverable content, the default selection behavior, and the calling context. Nothing an agent needs to invoke it correctly is missing.

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 baseline is 3. The description mentions finding_id omission and the site-wide page behavior, but those are already spelled out in the schema's own parameter descriptions, so it adds little semantic value beyond the structured fields.

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 states a specific deliverable: step-by-step fix instructions for one finding, including what to change, exact file:line locations, a before/after example, and a 'done when' check. That is far more concrete than the title and clearly separates this action tool from reporting/summary siblings like slop_report.

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 a clear usage mode ("work through a scan one problem at a time") and explains the no-finding_id fallback. It does not, however, name alternatives such as slop_rescue_plan or slop_report, nor state when not to reach for this tool, so it stops short of full routing 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?

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds useful context about what each guide contains, but says nothing about the size, structure, or return format of the content it pulls back.

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 with a colon-delimited list; every clause maps to a parameter value and carries information. No filler.

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 one-parameter documentation lookup with read-only annotations and no output schema, the description covers purpose and per-topic content adequately. Only the return format/size of the guide text is unaddressed, which is a minor gap.

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 0% and there is only one parameter, but the description compensates by explaining what each enum value actually yields (e.g., 'criteria' = every check with threshold and sources; 'playbook' = the full rescue method). That adds meaning beyond the bare enum list.

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?

States a specific verb (read) and resource (the reference guides behind AI Slop Meter), and enumerates the five distinct topics. An agent can immediately tell this apart from siblings like slop_scan, slop_rescue_plan, or slop_fix, which act on content rather than returning documentation.

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 enumeration of guide contents implies when each topic is useful, but there is no explicit when-to-use or when-not-to-use guidance relative to siblings (e.g., read 'criteria' before scanning, or 'playbook' before rescuing). Usage is inferred rather than directed.

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?

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds that the payload includes per-finding remediation steps and a done-when check, but says nothing about prerequisites (scan_id must reference an existing scan) or what happens when the page path is not in the scan. Adequate but not rich.

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?

Two sentences, no filler, with the content enumeration front-loaded before the usage hint. Efficient, though the second sentence is thin enough that it could have carried more routing value.

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?

There is no output schema, so the description usefully enumerates the return shape (score, categories, findings, steps, done-when check). For a read-only, single-object retrieval tool with fully documented parameters, that covers most of what an agent needs; only error/precondition behavior is missing.

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 scan_id, page, and lang are fully documented in the schema, including the enum and the default for lang. The description adds no parameter-level meaning beyond that, which is the expected baseline when the schema does the heavy lifting.

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?

States a concrete noun+scope: 'the full report for a single page of a site scan,' and enumerates what it contains (score, categories, findings, steps, done-when check). It implicitly contrasts with the site-wide sibling slop_report via 'a single page,' but never names an alternative, so it falls short of a 5.

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?

'Use it to work through a site page by page' gives a workflow hint, which is more than nothing, but there is no explicit when-not condition and no named alternative (e.g., use slop_report for the whole site, slop_fix to act on findings). Usage is implied rather than specified.

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?

Annotations mark it as a write operation (readOnlyHint=false) that is not open-world, and the description adds useful behavior beyond that: it writes an HTML file and may launch the user's browser, and browser launch requires prior user consent. It does not mention where the file lands, overwrite behavior, or failure modes, but the consent gating is meaningful added context.

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?

Front-loaded with the core verb and resource, followed by two short sentences covering timing and the consent rule. The parenthetical screen inventory is slightly verbose but it earns its place by describing report contents.

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 write tool with no output schema, the description covers what is produced, when to call it, and the one side-effectful parameter's consent requirement. The only notable gap is the undocumented target_score parameter, which an agent would have to infer.

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 75%, so the schema carries most parameter meaning; the description reinforces the permission condition on 'open' but adds nothing about 'lang'. Most notably 'target_score' has no description in either the schema or the description, leaving its effect on the report unexplained.

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?

States a specific verb+resource ('Write the visual HTML report for a scan') and even enumerates the report's screens, so an agent knows exactly what gets produced. It does not, however, differentiate itself from the sibling slop_scan_html, which by name also appears to emit HTML, leaving a real ambiguity unresolved.

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?

Gives clear timing guidance ('at the end of a rescue so the user finds the result waiting') and a conditional rule for the open parameter ('only if the user agreed'). No explicit when-not or named alternative is given, so the sibling routing question from slop_scan_html remains unanswered.

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?

Annotations only declare readOnlyHint and openWorldHint=false, so the description usefully adds that the output is a prescriptive, finding-linked plan with estimated score gains rather than raw analysis. It does not disclose cost, latency, whether it re-scans the site, or any limits on scan_id age, leaving the heavier behavioral burden partly unmet.

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?

Two sentences, front-loaded with the transformation and its outputs, closing with the follow-up loop. Every clause carries information and nothing is padded.

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?

With no output schema, the description does the work of explaining what the caller receives — a prioritised plan with findings, file:line references, and estimated score gain — which is exactly what an agent needs to decide whether the result is usable. Only the ambiguity about how this differs from sibling report/guide tools remains.

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% with clear per-parameter docs (keep, lang, scan_id with an example, target_score with a default), so the schema already carries parameter meaning. The description adds no extra syntax or semantics for these parameters, which is the expected baseline.

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 names a specific transformation (scan → prioritised, site-specific plan) and enumerates the concrete artifacts produced (quick clean-ups, copy rewrites, design direction, trust fixes), each tied to findings and file:line locations. This clearly distinguishes it from slop_scan (which produces the input) and the other report/guide siblings.

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 states the position in the workflow — turn a scan into a plan, then call slop_scan again to measure — which implies this runs after a scan. However, it gives no guidance on when to prefer this over slop_report, slop_fix, slop_guide, or slop_compare, which is the actual selection problem among eight siblings.

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?

Goes well beyond the annotations, which only say it is not read-only and is open-world. The description explains that a report file is always written even when open_report is false, that robots.txt is respected during crawling, that DESIGN.md triggers design-drift findings, and that repeat scans auto-compare. That is exactly the mutation/IO context an agent needs, and it also reconciles readOnlyHint=false.

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?

Front-loads the verb and the three target types, then return shape, then DESIGN.md/compare behavior, then the folder-vs-URL preference — a sensible priority order. Slightly bloated by the mid-sentence parenthetical framework list and the condensed one-sentence return contract, but no genuinely wasted sentence.

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?

With 8 parameters, no output schema, and only three terse annotations, the description carries the return contract itself: 0-100 score, five category scores, ranked findings with evidence/fix/file:line, and a separate AI-search-readiness score. Nothing an agent needs to call this correctly or interpret the result is missing.

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 every parameter (target, pages, render, ignore, lang, compare, open_report, include_ui_primitives) is already documented in the schema. The description largely restates target types and compare behavior rather than adding format, limits or tradeoffs beyond it, so the baseline 3 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?

States a precise verb (scan) with three explicitly enumerated resource types (URL, project folder with framework list, single .html file) and the exact defect class it hunts (generic copy, cliché phrasing, vibe-coded design, placeholder leftovers, missing trust signals). An agent knows immediately what this tool is for and how it differs from slop_compare/slop_fix/slop_report, which all consume rather than produce a scan.

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?

Ends with a clear routing rule: 'Prefer scanning the project folder when the user is working on the site's code; scan the URL for live sites,' plus 'Only pass true if the user agreed to this' for open_report. Clear when-to-use context, but no explicit exclusions or named sibling alternatives (e.g. slop_scan_html vs. the single-.html mode claimed here).

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?

The description adds real behavioral value by stating the output is the 'same report as slop_scan', which lets an agent reason about return shape without an output schema. However, it does not reconcile readOnlyHint=false with what is nominally a pure analysis operation, nor does it mention side effects, caching, or rate limits.

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?

Three short sentences, front-loaded with the core action and the disambiguation rule immediately after. No filler, no restating of the tool name.

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 four-parameter, single-required-input tool with no output schema, the description covers purpose, input routing, and output equivalence with a sibling. The only mild gap is the absence of any note about how large an HTML payload can be handled or what the caller should do with the result.

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 url, html, lang, and label are all documented in the schema (including the enum default and the before/after pairing use of label). The description adds no parameter-level detail beyond what the schema already provides, so the baseline of 3 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?

States a specific verb+resource (scan raw HTML for AI slop) and scopes the input modality to pasted or self-generated HTML. It explicitly distinguishes itself from the sibling slop_scan by naming which input types belong to each.

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?

Gives an explicit routing rule: use this tool for raw HTML, use slop_scan for URLs and folders. Both the 'when to use' and the named alternative are stated, leaving nothing to inference.

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