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

No annotations are provided, so the description carries the full disclosure burden, yet it says nothing about network fetching cost, how many requests it makes, whether it fails without sourcemaps, or how long a 25-chunk analysis takes. The only behavioral hint is the word 'forensically', which does not tell the agent what to expect operationally.

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 dense sentence with zero filler; the core action and the framework families are front-loaded. It is information-rich but slightly overloaded with parenthetical lists, which is acceptable given there is no other text.

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 complex analysis tool with no annotations and no output schema, the description names the deliverables at a high level (route topologies, state stores, inferred interfaces) but omits return shape, sourcemap dependency, and failure modes. It is minimally sufficient to select the tool but not to predict its output or cost.

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 both 'url' and 'maxScripts' are already documented in the schema, and the description adds no additional meaning such as what a script chunk is or how quality degrades below the default. Baseline 3 applies 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?

The description states a specific verb+resource pair ('forensically reconstructs client-side route topologies and global state stores') and names the frameworks it handles plus the artifacts it produces (TypeScript interfaces, action creators). It is clearly distinguished from a plain bundle decompiler, though it never explicitly contrasts itself with web_decompile_bundles or web_reconstruct_schema.

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?

There is no statement of when to use this tool, when not to, or which sibling to prefer. The agent must infer usage from the phrase 'forensically reconstructs', with no prerequisites (e.g. whether sourcemaps must be present) or alternatives named.

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 disclosure burden. It reveals the mechanism (fetching and scanning client-side JS bundles) and the output format, but says nothing about whether this issues many network requests to the target, how long or how deep the scan runs, whether it is passive or detection-prone, or what happens on unreachable/locked-down sites.

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 well-formed sentence with the mechanism and the deliverable front-loaded, no filler. It is compact, though the density means the scope constraints an agent needs are simply absent rather than condensed.

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 a one-parameter tool with no annotations and no output schema, the description does state the concrete return artifact (an OpenAPI 3.0 spec), which is the key missing piece elsewhere. Remaining gaps about scan scope and failure modes are real but modest for a tool this simple.

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?

Only one parameter and schema coverage is 100% ('Target website URL'), so the schema already does the work. The description adds nothing about what the URL should be — root origin vs a deep page path — which would materially change results, so this is baseline rather than above it.

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?

Specific verb ('Scans client-side bundles') plus a concrete deliverable ('comprehensive OpenAPI 3.0 specification of all internal, unadvertised API routes'). An agent can distinguish it from web_decompile_bundles or web_reconstruct_schema by the OpenAPI-route-catalog output, though those siblings are never named.

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?

There is no explicit when-to-use, when-not-to-use, or prerequisite (target reachability, auth, scope of crawl). Nothing steers the agent between this and adjacent siblings like web_reconstruct_schema or web_decompile_bundles, so selection is left entirely to inference from the noun phrase.

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, the description carries the full behavioral burden. It discloses useful facts (HAR 1.2 output, WebSocket replay server generation, live recording), but stays silent on side effects such as writing artifacts to disk, launching a browser, capture latency/cost, and whether the session is time-bounded by default. Slightly better than adequate but leaves meaningful gaps.

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 leads with the core action before listing capabilities, so the agent gets the gist immediately. The dense enumeration is slightly list-like but every clause corresponds to a real feature, so little is wasted.

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 an 8-parameter mutation tool with no annotations and no output schema, the description covers what the tool produces but omits operational context (disk writes, browser requirements, duration defaults, failure modes). It is minimally sufficient for an agent that reads the schema, but not self-sufficient.

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 all eight parameters are already documented, giving a baseline of 3. The description loosely maps its capability list onto flags (WebSocket recording, cookie/localStorage state), but it doesn't clarify the injection-vs-snapshot distinction or default behaviors beyond what the schema already states.

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 a specific verb+resource ('Captures live dynamic web sessions') and enumerates four concrete capabilities (HAR 1.2 capture, WebSocket frame recording, cookie/localStorage snapshotting, offline replay server generation). It is clearly distinguishable in intent, though it never names or contrasts against nearby siblings like web_clone_offline_mirror or web_inspect_pwa_cache.

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?

There is no explicit guidance on when to reach for this tool versus alternatives, nor any stated prerequisites (e.g. headless browser availability, permissions). The usage is implied by the capability list but an agent must infer the selection criteria itself.

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, the description carries the full burden and does disclose real behavior: it rewrites asset URLs to relative paths and injects a ServiceWorker/fetch mock so SPAs stay interactive offline. It omits important side-effect context — that it writes files to a local directory, what happens on failure or partial download, and the time/network cost of crawling.

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 no filler; every clause (offline mirror, URL rewrites, mock API interceptor, SPA interactivity) contributes distinct information. It is dense to the point of being a run-on, which slightly hurts readability.

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 and no annotations, so the description should state what the tool returns (a directory path? a manifest?) and note disk-write side effects. It explains the artifact well but leaves the return value and failure behavior unspecified.

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, maxAssets, outputDir, and includeMockApi are all documented in the schema. The description mentions asset crawling and the mock API injection conceptually but adds no syntax, format, or default detail beyond the schema, so 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?

Specific verb plus resource: 'clones a website into an interactive 100% offline-playable mirror', and it names the distinguishing mechanisms (relative URL rewrites, injected mock API interceptor). It never mentions how it differs from sibling tools like web_optimize_offline_cache or web_inspect_pwa_cache, so it stops 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?

There is no when-to-use guidance, no exclusions, and no named alternative. The agent must infer from 'offline mirror' alone whether this or web_optimize_offline_cache, web_capture_live_session, or web_inspect_pwa_cache is the right call.

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, the description carries the full burden. It says sources are reconstructed 'into clean directories,' which reads as always-on disk writes, while the schema's unpackToDisk parameter defaults to false — the description never clarifies that disk output is opt-in. It also omits network/auth requirements, scope of crawling, output size/volume, and whether anything is mutated or overwritten in outputDir.

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 no filler, leading with the primary action. It is dense — three capabilities packed into one clause chain — but nothing is redundant.

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 multi-stage tool with no annotations and no output schema, the description covers what it does but not what an agent needs to run it safely: whether the target must be publicly reachable, whether output goes to disk by default, and roughly what the result contains (file tree, endpoint list). Adequate but with visible gaps.

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 all four parameters including defaults are already documented in structured form. The description adds no extra semantics about url scope, chunk selection behavior, or what maxScripts truncation means in practice, 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?

Names three concrete operations with specific verbs and resources: decompiling Webpack/Vite/Turbopack JS chunks, reconstructing sources from sourcemaps, and carving internal API endpoints. The mention of modern frontend bundlers clearly separates it from siblings like web_decompile_wasm and web_decompile_shaders.

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?

No indication of when to reach for this tool versus alternatives such as web_clone_offline_mirror, web_diff_bundle_releases, or web_audit_api_catalog, even though the endpoint-carving capability overlaps with the latter. No prerequisites, no conditions, no exclusions are stated.

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, the description carries the full burden of behavioral disclosure. It does not state that the tool writes files to disk (via outputDir), overwrites existing artifacts, or requires specific permissions. The phrase 'synthesizes interactive 3D visualizers' hints at output generation but does not clarify side effects or safety profile.

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 a single, front-loaded sentence that efficiently lists the tool's capabilities without filler. It could be slightly more scannable (e.g., broken into bullet points), but it remains concise and informative.

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 tool with five parameters and no output schema, the description is missing key context about return values, file-writing behavior, and the relationship between the generateHtml/generateJson/generateMarkdown flags and the actual outputs. It covers what is analyzed but not what the agent should expect as a 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 the schema already documents all five parameters in detail. The description does not add any parameter-specific meaning beyond what the schema provides; it mentions file types that are already covered in the target parameter's description.

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 verb ('decompiles') and a precise resource scope: 3D graphics and shader pipelines, covering GLB chunks, glTF materials, GLSL/WGSL shaders, engine fingerprinting, and visualizer synthesis. This clearly distinguishes it from sibling tools like web_decompile_bundles (JS bundles) and web_decompile_wasm (WebAssembly).

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 usage for 3D/shader content by naming the file types and analysis tasks, but it provides no explicit guidance on when to choose this tool over alternatives such as web_decompile_bundles. No exclusions or prerequisites are mentioned.

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, so the description carries the burden: it usefully reveals that the tool writes multiple artifact files, carves embedded strings/secrets from data sections, and produces a self-contained interactive HTML report — non-obvious side effects worth knowing. It omits whether outputDir is created or overwritten, whether URL targets require network egress, and whether the operation is purely read-only against the source target.

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 led by the action verb, with the artifact list appended in priority order. Dense but every clause names a distinct capability that maps to a required flag or output; nothing is 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 7-parameter tool with no annotations and no output schema, the description does explain the generated artifacts, which is the main unknown. It leaves gaps on filesystem side effects (overwrite behavior of outputDir), network requirements for URL targets, and what the tool returns to the caller, which an agent needs before invoking it in a loop.

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% with per-parameter descriptions and defaults, so the schema already documents target, outputDir, and all five generate* toggles. The description restates that these outputs exist but adds no syntax, format, or default rationale beyond the schema. 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?

Opens with a specific verb ("Decompiles") and named resources (WebAssembly binaries or carved Base64 WASM modules), then enumerates the concrete artifacts produced (WAT, .d.ts interfaces, host loaders, carved secrets, HTML explorer). An agent immediately knows what it does and what it emits, though it never distinguishes itself from the adjacent web_decompile_bundles or web_decompile_shaders 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?

Usage context is implied by the accepted inputs (a .wasm file or a JS bundle/HTML containing embedded Base64 WASM), so the agent can infer this is the tool to reach for when the WASM payload is the target rather than the surrounding bundle. There is no explicit when-to-use / when-not guidance and no pointer to the decompile-bundles or decompile-shaders alternatives.

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, the description carries the full burden: it discloses that reports are generated (visual regression and breaking change), which hints at filesystem writes, but omits whether live URL targets require auth/network access, cost or timing implications, and whether output artifacts are overwritten in outputDir.

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 packs the operation, inputs, and output artifacts without filler. It is dense but readable; slightly long as one sentence but nothing is wasted.

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 6-parameter, multi-artifact tool with no annotations and no output schema, the description defines the analysis scope well but leaves gaps: what the returned result looks like (paths vs. summary), behavior when targets are unreachable, and any side effects on an existing output directory.

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 all six parameters already have documented semantics and defaults. The description's parenthetical '(local directories or live URLs)' corroborates baseTarget/currentTarget but adds no format, constraint, or interaction detail beyond 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?

States a specific verb ('compares') and resource ('two client web releases') plus the artifacts it derives (chunks, endpoints, routes, components, reports). An agent can tell this apart from siblings like web_decompile_bundles or web_analyze_app_state, though it doesn't name those siblings explicitly.

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 requirement of two targets (baseline + current), but the description never states when to use this versus web_decompile_bundles, web_audit_api_catalog, or web_analyze_app_state, nor any prerequisites such as access to a live URL.

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 at all, the description carries the full behavioral burden. It does disclose the substantive output—design tokens plus standalone JSX—but says nothing about network behavior, timeouts, auth requirements, whether rendering is headless, or how partial failures are reported for what is clearly a remote-fetch operation.

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 dense sentence that front-loads the two output artifacts and ends with the use case. It is efficient, though the parenthetical lists make it slightly overloaded for one 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?

For a two-parameter tool with no output schema and no annotations, the description should pin down the return shape (e.g., tokens as JSON plus JSX as string, single vs. multiple files). It gestures at the outputs but leaves the response structure and failure modes unspecified.

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 both parameters are already documented, making 3 the baseline. The description does add modest value by illustrating selector values ('header, hero, nav'), but does not clarify accepted selector syntax (CSS selector vs. tag name) or what happens when the selector matches nothing.

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 pairs specific verbs with specific artifacts: extracting design tokens (colors, font hierarchy, Tailwind theme) and converting DOM elements into standalone React JSX components. It is far more informative than a tautology, but it never names or contrasts with the closest sibling, web_synthesize_shadcn, which likely also emits components.

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?

There is no statement of when to reach for this tool versus alternatives such as web_synthesize_shadcn or web_clone_offline_mirror, and no preconditions (e.g., site must be publicly reachable, JS-rendered content). The only hint of context is the phrase 'for immediate vibe coding,' which signals intent but not selection criteria.

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, the description carries the full burden. It implies file generation but does not disclose side effects such as whether outputDir is overwritten, whether network access to target is required, or what happens to existing files. It also omits any return-value or error behavior.

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 single sentence is front-loaded with the core action and lists outputs efficiently. It is dense but every clause contributes to scope, with no obvious 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 six-parameter generation tool that writes files and produces multiple artifacts, the description is missing key operational context: preconditions, whether it writes to disk, overwrite behavior, and what the caller receives. No annotations or output schema exist to fill those gaps.

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 schema already documents every parameter including defaults and allowed framework values. The description does not add parameter-level meaning beyond what the schema provides, so the baseline of 3 is appropriate.

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-plus-resource construction: extracts routes/forms/API schemas to synthesize Playwright and Cypress E2E suites, mocks, simulator, and runner. This clearly distinguishes it from sibling tools like web_audit_api_catalog or web_synthesize_shadcn.

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 what the tool generates but gives no guidance on when to choose it over alternatives such as web_audit_api_catalog or web_analyze_app_state. There are no exclusions, prerequisites, or contextual triggers for use.

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 behavioral burden, yet it reads as a feature list. It never states whether 'target' as a URL triggers live network access, what permissions are needed, whether WebSocket frames are captured live or read from disk, or what the generated artifacts contain beyond their filenames. The composite, potentially heavyweight nature of the tool is undisclosed.

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?

It is a single sentence with no filler words, but it is a dense, comma-chained list of four capabilities rather than a front-loaded statement of purpose. The agent must parse the whole run-on to extract what the tool does, and the visualizer clause adds length without routing information.

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 five parameters, no output schema, and no annotations, the description should explain behavior and outputs more fully. It covers the capability surface and the schema covers the flags, but how the target is consumed, what capture is required for WebSocket input, and what the audit artifacts report are left implicit.

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 all five parameters, including the three generate flags and outputDir, are already documented in the schema. The description adds no syntax or format meaning beyond that, 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?

The description uses specific verbs and named resources: 'decompiles... CRDT state synchronization protocols (Yjs, Automerge, Liveblocks, ShareDB),' 'decodes binary vector clocks,' 'reconstructs document state trees.' This is far more concrete than a tautology, but it stacks four distinct capabilities into one tool, making it hard to know the single primary action, and it never names a sibling it differs from.

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?

There is no explicit when-to-use guidance, no prerequisites, and no exclusions. An agent cannot tell from the text when to pick this over web_decompile_bundles or web_analyze_app_state, which plausibly overlap with bundle and app-state inspection.

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 behavioral burden and falls well short. It doesn't say whether a URL target triggers live network fetches, whether authentication or cookies are required, whether any target files are modified, or what happens when no manifest is found. Only the target description hints that local folders and remote URLs are both accepted.

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 dense sentence with no filler, front-loaded on the core capability. It is jargon-heavy (PSSH, EME, ABR ladder) but each clause names a real, distinct audit dimension rather than padding.

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 schema covers outputs and flags, so the description needn't restate them, and there is no output schema to explain. But for a tool that fetches remote manifests and emits artifacts, the absence of any note on network access, safety, or failure modes leaves a meaningful 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 description coverage is 100%, so all five parameters are already documented with defaults and types. The description adds nothing about parameter behavior (e.g., how outputDir interacts with the three format flags, or what 'target website URL' crawling entails), 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?

Concrete verbs (decompiles, reconstructs, decodes, audits) applied to a specific resource: HLS/DASH streaming pipelines, segment timelines, ABR ladders, PSSH boxes, EME APIs. The domain is unambiguous and clearly distinct from siblings like web_decompile_bundles or web_decompile_wasm, though it never explicitly distinguishes itself from them.

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?

No statement of when to pick this tool over web_decompile_bundles, web_capture_live_session, or web_analyze_app_state, all of which an agent could plausibly confuse with media pipeline analysis. No prerequisites or trigger conditions given.

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 behavioral burden, yet it does not state whether the tool is read-only, what network or filesystem access is required, or that it writes audit artifacts to outputDir. It also does not address the sensitivity of extracting unencrypted credentials beyond naming the capability.

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 a single long, comma-heavy sentence that lists many capabilities without structural breaks. It is compact and front-loads the manifest audit, but the run-on enumeration makes it harder to scan than a deliberately structured summary.

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 schema fully documents all seven parameters, which reduces the description's burden, and the description does enumerate the main inspection capabilities. However, with no annotations and no output schema, it still omits prerequisites, side effects, and how the generated artifacts should be interpreted, leaving meaningful context gaps for a multi-feature audit 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?

Schema description coverage is 100%, so every parameter including target, outputDir, and the generate/inspect flags is already documented in the input schema. The description adds no parameter-specific meaning beyond the operation names that the schema also covers, so the baseline of 3 is appropriate.

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 specific verbs and resources — auditing Web App Manifests, reverse-engineering ServiceWorker caches, extracting IndexedDB schemas — so the tool's scope is clear. However, it bundles several capabilities into one sentence and never distinguishes itself from siblings such as web_optimize_offline_cache, web_reconstruct_schema, or web_analyze_app_state.

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?

There is no explicit guidance on when to use this tool, when not to use it, or which sibling to choose for adjacent tasks like offline caching optimization or schema reconstruction. The intended use case is only implied by the tool name and by the listed inspection targets.

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, the description carries the full burden. It does disclose real behavior beyond the schema: output is content-addressable assets written to outputDir, deduplication uses hard links, compression produces .gz/.br files, and an optional preview server can be launched. However, it never says whether the source target is modified in place, whether network access is required for URL targets, or what the tool returns (server URL, summary report, nothing), which are the traits an agent most needs for a mutating, 7-parameter tool.

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?

It is a single sentence, so it is compact, but it is a run-on that front-loads jargon ("SHA-256 Content-Addressable Storage (CAS)") and marketing adjectives ("built-in high-performance") instead of the one thing an agent needs first: when to call this and what it produces. Signal-to-noise is mediocre.

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?

Seven parameters, no annotations, and no output schema — a case where the description must compensate, and it does not. The most consequential unknown is the return value: if startPreview is true, does the tool return the bound port/URL? The description also leaves open whether the tool is safe to re-run and whether it mutates the target directory.

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 every parameter including defaults is already documented in the schema. The description only restates the same concepts (deduplication, pre-compression, preview server) at a higher level without adding format, interaction, or constraint detail. 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?

The opening clause states a verb and resource ("Optimizes offline site mirrors"), which is intelligible, but the rest is a feature inventory (CAS, Brotli/Gzip, HTTP/2 preview server) rather than a statement of purpose. Nothing distinguishes it from a sibling like web_clone_offline_mirror or web_inspect_pwa_cache, so an agent cannot confidently route between them from the text 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?

There is no when-to-use guidance, no prerequisites (does target need to already be a mirror, or can it be a live URL?), and no named alternative. The description reads as a capability list rather than invocation 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, the description carries full behavioral burden. It mentions generating reports and artifacts but omits key operational traits: whether it requires network access, executes scripts in a browser, handles authentication, has rate limits, or what permissions are needed. For a tool that writes files to outputDir, these gaps are significant.

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 a single dense sentence that front-loads the core purpose and then lists secondary capabilities. It is information-packed but not repetitive; however, the long enumeration could be slightly streamlined without losing 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?

For a complex tool with six parameters, no output schema, and no annotations, the description covers what the tool does and what artifacts it generates, but it lacks operational context such as environment requirements, failure modes, or security implications. It is sufficient to understand the tool's purpose but not fully complete for safe invocation.

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 schema already documents all six parameters thoroughly. The description does not add meaning beyond what the schema provides for any parameter; it only reiterates high-level capabilities already implied by the parameter names.

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 ('Profiles') and enumerates the exact resources (Canvas 2D, WebGL/GPU, AudioContext, etc.), plus additional actions like detection, entropy calculation, and report generation. This clearly distinguishes it from sibling tools such as web_decompile_shaders or web_recon_infrastructure.

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 the tool is for auditing client-side fingerprinting and anti-bot telemetry, but it never states when to use this tool versus alternatives or when NOT to use it. No explicit prerequisites or exclusions are given.

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 behavioral burden. It does not disclose whether the scan is passive or active, whether it touches the target in an intrusive way, rate limits, authentication requirements, or what the result looks like; it only lists analysis categories.

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 definition is a single front-loaded sentence with no filler. Every listed domain contributes to the tool's scope, and the target is stated immediately.

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 broad forensics tool with no annotations and no output schema, the description is too thin about what an agent will get back, how deep or slow the scan may be, and any scope limitations. It names analysis areas but does not complete the operational picture.

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 single 'url' parameter is fully documented in the schema, including an example, so the description does not need to repeat its type or format. It also adds no extra parameter semantics beyond the schema, making the high-coverage baseline of 3 appropriate.

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 action (performs deep forensics) and enumerates concrete resource areas: infrastructure, Edge/CDN, WAF, DNS, TLS, security headers, and frontend frameworks. That is clear enough to distinguish it from siblings like web_decompile_bundles or web_inspect_pwa_cache, though it does not explicitly name alternatives.

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 'on any target website URL' and by the listed forensic domains, but there is no explicit when-to-use, when-not-to-use, prerequisite, or sibling routing guidance. An agent must infer that this is the broad infra reconnaissance option.

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, the description carries the full burden. It helpfully discloses the exact artifacts produced and their formats, implying filesystem writes, but says nothing about whether the target URL is fetched live, permission/auth needs, reversibility of writes to outputDir, or the cost of processing bundles. Useful but materially incomplete for a multi-parameter generation tool.

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?

One front-loaded sentence beginning with the verb, with no filler. It is dense and slightly run-on due to the artifact list, but every clause (sources, output formats, artifact names) earns its place.

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 7-parameter tool with no output schema and no annotations, the description covers what is produced (substituting partly for a return-value section) and the range of acceptable targets. It omits prerequisites such as whether network access to the target is required and what happens on partial/failed reconstruction.

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 every parameter is already documented in the schema, setting baseline 3. The description's enumeration of output artifacts loosely maps to the generate* flags but adds no meaning beyond what the schema already says (defaults, accepted target types).

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 ('Reconstructs') and precise resources: GraphQL SDL, gRPC-Web proto3 interfaces, derived from client bundles/AST queries/wire frames. The named artifacts (schema.graphql, service_definitions.proto, visualizer) clearly separate this from siblings like web_decompile_bundles or web_audit_api_catalog, which extract rather than reconstruct schemas.

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 context by listing input sources (bundles, AST queries, wire frames), which loosely signals when the tool applies. But it never names an alternative sibling or states when not to use it, leaving the agent to infer that this is the schema-reconstruction option among many extraction tools.

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 behavioral burden and it falls short: it doesn't say whether the tool fetches the URL over the network, how long generation takes, whether it writes files or returns code inline, or what the response looks like. It only names the technology stack and the dark-mode/Lucide/Storybook synthesis capabilities, which largely mirror the parameter 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?

A single front-loaded sentence with the output artifact stated first and the input source last. Dense with tech-stack names but every clause adds identification value; no filler or repetition.

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 (all optional), no annotations, and no output schema, the description does not need to restate parameter details but should state what is produced. It names the component output and stack but not the return shape (inline code string vs. file set vs. object with stories). Minor gap rather than a blocking one given the 100% schema coverage.

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%, including defaults and examples, so the schema does the heavy lifting. The description restates dark-mode variants and Lucide mapping without adding format, precedence (url vs html), or selector semantics beyond what the schema says. 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 specific verb ('Synthesizes') and a concrete output artifact (TypeScript React components using Shadcn UI, Radix, Lucide, Tailwind) from a specific input (URL or raw HTML subtree). An agent can tell it's a code-generation tool, not a recon or decompilation tool. It doesn't explicitly differentiate itself from the closest sibling, web_extract_vibe_components.

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?

No when-to-use / when-not-to-use guidance and no named alternatives, despite a crowded sibling set (web_extract_vibe_components, web_clone_offline_mirror, web_generate_e2e_harness) where routing matters. The only implicit guidance is that either a URL or an HTML string can be supplied.

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