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

With no annotations, the description carries the behavioral burden and does state what the tool returns ('structured TrafficSummary items with matched_fields and match_reasons') and that it produces compact summaries. It does not explicitly label the operation as read-only or mention side effects, but 'analyze' and 'saved recording snapshot' make the non-mutating intent clear enough.

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?

Every sentence adds a distinct piece of guidance: what it does, when to use it, what to prefer instead, what to preserve, what it returns, and how to drill down. The content is front-loaded and there is 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?

Given an output schema exists, the return-value mention is a bonus, and the description covers usage context, alternatives, and follow-up workflow. It falls just short of fully complete because it never explicitly states that recording_path must be supplied to select the recording, despite all parameters being marked optional in the schema.

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 0% across 23 parameters, and the description only adds meaning for recording_path ('preserve it for follow-up detail calls'). The many filter parameters (host_contains, path_contains, status_in, etc.) rely entirely on their names, so the description does not compensate for the lack of schema documentation.

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 first sentence names a specific verb and resource ('Analyze a saved recording snapshot') and the qualifier 'with compact summaries' clarifies its scope. It explicitly labels itself as the history-plane tool and names live-capture siblings, so an agent can distinguish it from the cluster of live and reverse tools without inspecting 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?

Gives an explicit precondition ('only use when the user explicitly references a saved recording (.chlsj file)') and explicit alternatives for live traffic ('start_live_capture + query_live_capture_entries'). It also tells the agent to preserve recording_path for follow-up and to use get_traffic_entry_detail for drill-down, which is exactly the routing guidance needed.

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 disclosure burden. It discloses that the tool returns a recommended_next_action and ties that to the active-capture state, which is useful behavioral context. However, it does not explain what happens when Charles is unreachable/not connected, or whether this is a read-only operation—gaps that matter given annotations are absent.

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 two tight, purposeful sentences with no waste. The first sentence front-loads the tool's purpose, and the second gives actionable context, making it easy to scan.

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 parameterless status tool with an output schema, the description covers the essential decision logic and names the relevant sibling tools. It does not list the exact return fields or enumerate all error conditions, but the output schema presumably handles field-level detail and the description provides enough context for correct 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?

The tool has zero parameters, so the baseline is 4. The description does not need to explain any parameter semantics, and nothing about the schema coverage lowers this bar.

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 begins with a specific, actionable verb 'Check' and names the exact resource ('Charles connectivity and active live-capture state'), which immediately clarifies the tool's function. It also differentiates from siblings by referencing start_live_capture and the broader history-plane tool family, so an agent can tell this status check apart from capture management or replay tools.

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 provides explicit routing guidance: when no active capture exists, agents should call start_live_capture before falling back to history-plane tools. This both tells when using this tool is appropriate and directs the agent to the correct sibling tools under a specific condition, satisfying the when/alternative requirement.

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 must carry behavioral disclosure, but it only states the action without any side effects, limits, or operational behavior. It does not explain how 'coarse' numbers are produced or what happens with large capture_id sets, and the scan_limit parameter is absent from the text.

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 one focused sentence with no wasted words and front loads the core action. While it is terse, it is not bloated or redundant, which earns a score above average despite sacrificing details that might help.

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, conditional requirements (capture_id vs recording_path depending on source), and no annotations, the description is far too thin to guide a correct call. An output schema exists, but the description still fails to cover the input dependencies and choice boundaries.

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 0%, so the description should compensate by explaining the five parameters. The only hint is 'live capture or saved recording', which loosely maps to source and capture_id/recording_path, but the roles of preset, capture_id, recording_path, and scan_limit are left unexplained, leaving agents guessing about required inputs.

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 action (return) and a clear resource (coarse traffic class counts) with an explicit scope ('live capture or saved recording'), which separates it from entry-level tools. It does not explicitly contrast with sibling tools, but the core function is unambiguous.

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 guidance about when to choose this tool over closely related siblings such as get_recording_snapshot, query_live_capture_entries, or group_capture_analysis. It also fails to mention prerequisites or the conditions under which live vs saved recordings should be used.

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 full behavioral burden. It discloses that the tool does not read the live capture and is a history-plane tool, but it does not explicitly state whether loading is side-effect-free, read-only, or whether internal state is modified. More detail on side effects or read-after-load behavior would be needed for full 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?

The description is three sentences long and every sentence adds value: the primary action, the distinction from live session, and the trigger for use. It is front-loaded with the core action and uses plain, unambiguous language with minimal fluff.

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 is simple, has an output schema, and the description provides strong guidance on when and how to use the tool, plus a useful negative (no live access). However, the path parameter remains undocumented, and the default/required behavior is not explained. Given the lack of annotations, this minor gap keeps it from being fully complete for an AI agent.

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 0%, so the description must compensate; it mentions save as .chlsj files but never directly maps the path parameter to a file path or explains its meaning. The schema only offers a nullable, foreign path with a default of null. An agent is left guessing whether path is required, what format it should take, or how the default is resolved.

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 loads a saved recording snapshot and explicitly distinguishes it from live-session tools by asserting it never reads the live Charles session. It also specifies the file type (.chlsj), which helps an agent identify both the resource and the input type. This is specific and separates it from sibling live-capture and recording-analysis tools.

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 explicit when-to-use guidance: only when the user references a saved recording (.chlsj file). It also clearly states a when-not condition: 'never reads the live Charles session'. While it does not name a specific alternative tool (e.g., read_live_capture), the contextual boundary is strong enough for an agent to select or avoid it.

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 burden. It discloses that the tool requires a prior call and that include_full_body should be kept false unless needed, but it does not mention what the detail view contains, whether it is read-only, or any side effects. It is a read-like operation but that is not explicitly stated.

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 compact and front-loaded with the core purpose, followed by practical usage instructions. Every sentence adds value, and the guidance is easy to scan.

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 the tool has an output schema and the description covers the key usage flow, it is mostly complete. The main gap is the lack of explicit read-only/safety context and no mention of max_body_chars semantics, but the description is strong for a detail-inspection 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 0%, so the description must compensate. It explains the meaning of entry_id, recording_path, capture_id, and include_full_body in context, which is valuable. However, it does not explain max_body_chars or the source enum beyond the live/history distinction, leaving some parameters under-specified.

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 loads one traffic entry detail view for drill-down inspection, with a specific verb and resource. It distinguishes itself from bulk browsing and references prior summary/query calls, making its purpose unambiguous.

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 explicitly says when to use it ('for one confirmed target, not bulk browsing'), how to obtain required IDs ('from a prior summary/query call'), and how to handle live vs history entries. It also gives a clear directive on include_full_body, which is actionable 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?

No annotations are provided, so the description must carry the burden of behavioral disclosure. It mentions 'lower token cost' as a benefit, which is useful, but does not clarify key behaviors such as whether the operation is read-only (likely), whether data is consumed or cached, or what the output structure contains. The description is too terse to provide adequate transparency for a complex analysis 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?

The description is one sentence, which is concise and front-loads the primary action ('Group') and benefit ('inspect hot spots'). However, its brevity sacrifices necessary detail, making it more under-specification than optimal conciseness. It earns points for being short and focused.

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 the tool's high complexity (25 params, many filters and grouping options) and the lack of parameter descriptions, the description is incomplete. It provides no guidance on required parameters, preset semantics, or filter usage. The presence of an output schema helps but does not compensate for the absence of operational context.

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?

With 25 parameters and 0% schema description coverage, the description must compensate by explaining parameter usage, but it does not. The description only mentions the concepts of grouping and hot spots, leaving all parameters (e.g., 'group_by', 'preset', filters) and their relationships unexplained. This is a significant gap given the schema's lack of descriptions.

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 clear verb and resource: 'Group analyzed traffic' to help the agent inspect hot spots, which conveys the core function. However, it does not differentiate from sibling tools like 'get_capture_analysis_stats' or 'query_recorded_traffic', which may also operate on analyzed traffic, leaving potential ambiguity.

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 a hint of when to use it ('so the agent can inspect hot spots') but provides no explicit guidance on when to prefer this over alternatives or when not to use it. It lacks mention of specific scenarios or exclusions, leaving the agent to infer usage from the tool name and schema.

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 burden. It implies read-only behavior via 'List' and mentions returning recording_path, but does not explicitly state side effects or confirm it is non-mutating. It also doesn't describe output structure, though an output schema exists. 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?

Three sentences, no fluff. The core purpose is front-loaded, usage guidance is explicit, and the follow-up step is concise. Every sentence 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?

Given zero parameters and an output schema, the description is largely sufficient. It clarifies the tool's place in the history plane and provides next steps. Minor gap: it doesn't explicitly state it's read-only or list all recordings without filters, but that's inferable from the name and context.

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?

Zero parameters, so schema provides no details; baseline is 4. The description adds no parameter-specific info (none needed), but it does mention 'recording_path' in a usage context, which hints at what output might contain.

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 lists saved recording files (.chlsj files), with a specific verb ('List') and resource. It differentiates itself from live capture tools by explicitly naming the history plane, making it distinct from siblings like start_live_capture.

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?

Explicitly states when to use (only when user references saved recordings) and when not to (prefer start_live_capture for live traffic). It also gives a follow-up instruction to preserve recording_path for later calls, guiding the agent's workflow.

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 full behavioral burden. It discloses important side effects: a previous mock at the same path is archived, never deleted, and Map Local always answers 200 while ignoring method and query. It also points the agent to read the warnings field.

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 sentences, each earning its place: main purpose, source selection, and behavioral caveats. The most important information is front-loaded, and there is 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?

With 5 parameters, no annotations, and an output schema, the description covers the critical usage decisions, side effects, and response caveats. It doesn't cover error cases or exact entry_id format, but it is sufficient for correct invocation in common flows.

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 only 20%, so the description must compensate. It explains how entry_id is obtained from either capture_id or recording_path, and clarifies the source-dependent parameter usage. Patches are already well documented in the schema with JSON Pointer examples.

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 and resource: 'Turn a captured response into a Map Local mock, optionally editing it.' It also clarifies the source of the entry_id, which distinguishes this tool from rule-based mock creation siblings like mock_rule_create_from_entry.

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 clear context for when to use it: after query_live_capture_entries or a history summary, and explains which parameter to pass for each source. It doesn't explicitly name alternatives or exclusions, but the source-selection guidance is actionable.

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 behavioral burden and does so well: it discloses the grouping keys, the default /action field, the 'null' behavior for GETs and bodies without that field, and the live-source dependency. It stops short of explicitly stating that this is a read-only aggregation, though 'Overview' strongly implies it.

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 dense sentences deliver the full picture with no filler. The main grouping result is front-loaded, followed by usage timing, filters, and the live-source caveat, all in compact, scannable prose.

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 output schema covers return values, and the description covers main usage, filters, and the live caveat. But it never explains how history source relates to recording_path, and optional parameters like limit and max_groups are only known by their schema titles. Given 9 parameters and a required source enum, this leaves a meaningful gap for correct 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 0%, so the description must compensate. It explains body_field's default and semantics, names host_contains/path_contains/methods as filters, and notes capture_id's role for live. However, it leaves recording_path, limit, max_groups, and the history source semantics unexplained, so the compensation is only partial.

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 concrete behavior: an overview of the whole captured session, with requests grouped by method, host, path, and request-body field, plus counts, sample entry_ids, and response statuses. This is specific enough for an agent to distinguish it from sibling tools that analyze individual entries or signatures.

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 timing ('right after reading a session'), the main filters to apply, and the condition that live requires capture_id. It does not name sibling alternatives or state when not to use it, but the use context is clear and actionable.

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 full burden of behavioral disclosure. It discloses key lifetime behavior (dispatcher stops with the server), side effects (start/stop toggles Map Remote), and persistence of mock files. It does not address potential issues like port conflicts or overlapping instances, but it covers the most important operational side effects.

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 concise sentences with no fluff. The main purpose is front-loaded in the first sentence, and additional behavioral details follow logically. Every sentence adds value, making it highly efficient.

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 an output schema, so return values are already captured. The description covers the action semantics, side effects, and the alternative for long-running use. The only missing piece is a clear explanation of the `port` parameter, which is a minor gap given the tool's simplicity. Overall, it is complete enough for an agent to call it 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 0%, so the description must explain parameters. It explains `toggle_map_remote` by referencing its default behavior, and `action` is self-evident from the enum. However, `port` is never explained beyond its name; the description doesn't clarify what a port value does, its default meaning when null, or constraints. This is a significant gap given the lack of schema documentation.

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 explicitly states the verb and resource: 'Start, stop or check the local dispatcher that Map Remote routes point to.' This clearly distinguishes it from siblings like charles_status (general status) and mock_* tools (mock content) by narrowing to the dispatcher lifecycle.

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 provides clear usage context: it explains the dispatcher is short-lived within the MCP server and directs users to the `charles-mcp-dispatcher` command for long-running instances. It does not explicitly contrast with other mock tools, but the alternative for a distinct scenario is given, which is sufficient for routing.

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. 'Show' implies read-only, but this is not explicit, and there is no mention of side effects, required permissions, or limitations (e.g., only active mocks are accessible). The description adds minimal behavioral 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?

The single sentence is extremely brief, which is concise in word count, but it is under-specified for a tool with three parameters and no annotations. It front-loads the core purpose but omits crucial context, making it ineffective rather than appropriately concise.

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 an output schema (which covers return values), the description is severely incomplete. It does not explain the purpose of max_chars, any constraints on host/path format, or when to prefer this over sibling tools. An agent with only this description would struggle to use 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?

The description does not add any parameter-level meaning. The schema covers host and path (67% coverage), but max_chars is left undefined in both the schema description and the tool description. The description fails to clarify how parameters affect the output or behavior.

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 clear verb ('show') and resource ('content of one active mock'). It implies a specific fetch operation, distinguishing it from mock_list which likely lists all mocks. However, it does not explicitly mention the identifying parameters (host/path), but the schema covers that.

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 guidance is given on when to use this tool versus alternatives like mock_list or mock_write. It does not mention prerequisites, typical scenarios, or exclusions. The agent is left to infer usage from the schema.

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 full burden for behavioral disclosure. It adds the useful trait that archived versions are not listed, which prevents an agent from expecting them. However, it does not explicitly state that this is a read-only operation or mention any other side effects, permissions, or rate limits. For a list operation, this is a moderate gap, hence a 3.

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 two sentences, front-loaded with the core action and filter option, and the archived-exclusion note is concise and valuable. Every word earns its place; there is no redundancy or unnecessary elaboration.

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 list tool with one optional parameter and an output schema, the description covers the key points: what it lists, the filtering capability, and the exclusion of archived versions. The output schema handles return details, so no further explanation is needed. It could be a 5 if it explicitly stated read-only behavior or prerequisites, but it remains sufficiently complete for an agent to invoke 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?

The schema description coverage is 0%, so the description must compensate. It does so by explaining that the 'host' parameter filters the list to one host. This adds meaning beyond the raw schema (which only shows the type and default), enabling the agent to use the parameter correctly. It could be a 5 if it gave more detail (e.g., exact host format), but it covers the essential semantics.

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 ('List') and a distinct resource ('active mock files'), and explicitly excludes archived versions. This clearly distinguishes it from sibling tools like mock_rule_list (which lists rules) or mock_get (which retrieves a specific mock). The scope is unambiguous.

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 clear context: it lists active mock files and optionally filters by one host. It does not explicitly mention when to use it instead of other tools (e.g., mock_get for a single mock), but the resource type is distinct enough that an agent can infer appropriate usage. It lacks explicit exclusions or alternatives, so it falls short of 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?

There are no annotations, so the description correctly takes on the burden of explaining side effects. It states that the file moves to the archive and that requests pass through to the real server again, which is meaningful behavioral context beyond the tool name. It does not mention permissions or restore options, but the core mutation behavior is disclosed.

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, compact sentence front-loads the action and then gives concrete consequences. It contains no filler and does not repeat schema information, making every word earn 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?

This is a simple two-parameter tool with fully documented inputs and an output schema present. The description covers the trigger condition, the effect on the mock file, and the runtime effect on requests, which is complete for this operation.

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 both parameters fully documented including examples and caveats. The description reinforces that the operation affects a single path, matching the 'path' parameter, but adds no new parameter-level detail. Baseline 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, 'Stop mocking', and a specific resource, 'one path', then states the consequence. This clearly distinguishes it from related operations like mock_set_enabled or mock_rule_remove even without naming 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?

The phrase 'Stop mocking one path' clearly signals when to use the tool: when a mocked path should no longer be intercepted. It does not explicitly name alternatives, but the pass-through consequence provides enough context for an agent to understand the intended 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?

With no annotations, the description carries the full behavioral burden and does so thoroughly: it discloses config mutation, the Charles overwrite-on-quit risk, that this tool never quits or starts Charles, and that unmocked requests pass through unchanged. This gives an agent the critical side-effect and safety context needed before invoking the 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?

Every sentence earns its place: the mapping mechanism, pass-through behavior, config-write caveat, and exact user workflow are all essential. The most critical warning about Charles being closed is front-loaded, and there is no filler or redundant restatement.

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 a user-interaction workflow and config mutation, the description covers the prerequisites, apply modes, and pass-through behavior well. The missing port/verify_tls semantics and lack of explicit sibling differentiation are the main gaps, but the core workflow is fully described and an output schema exists.

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?

Host and path are already documented in the schema, and the description adds useful routing semantics for them. However, port and verify_tls have no schema descriptions and are never mentioned in the description, so with only 40% schema coverage a significant parameter-meaning gap remains.

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 clear operation: send a host/domain glob through the dispatcherorphan via a Charles Map Remote mapping, covering every path and action under that host. The 'once per host/domain' scope makes the resource and purpose specific, though it does not explicitly distinguish itself from the similarly named sibling mock_setup_host.

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 strong operational guidance: use apply=true only while Charles is closed, ask the user to save and quit, and avoid reopening Charles until the write completes. It also explains that apply=false provides manual UI steps without a restart, but it does not explicitly name when to prefer this tool over related 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?

With no annotations, the description carries the full behavioral burden. It discloses mode semantics (patch vs fixture), that patch mode contacts the server while fixture uses the captured response, merge behavior (adds to existing rule, replaces on same pointer), host_scope handling, match_path coverage requirement, and that patches are validated against the entry. It does not cover error conditions or side effects beyond 'create or extend', but covers the key runtime behavior well.

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 long (~180 words) but justified for a 19-parameter tool. It front-loads the purpose and then systematically covers parameters. Some sentences, like the match_path example, are dense but add clarity. It could be slightly tightened, but it is well-structured and each sentence contributes to understanding.

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 description covers the core behavior and most key parameters, but leaves several parameters undocumented (priority, description, capture_id, recording_path, match_query_fields) and assumes the agent understands what an 'entry' is and how to obtain entry_id from sibling tools. Given the tool's complexity, an agent might need to consult other tools or schema for full context, but the description is adequate for the primary use case.

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?

Given only 21% schema description coverage, the description compensates by explaining most critical parameters inline: match_body_fields (with example), host_scope (any/exact/host glob), match_path (pattern semantics and example), mode, status, delay_ms, merge, request_patches, response_patches, and request_headers. It adds meaning beyond the schema, though a few parameters (capture_id, recording_path, match_query_fields, priority, description) remain 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?

The description opens with a clear, specific statement: "Create or extend the rule for one request variant (method + path + body/query values) from a captured entry." It names the verb ('create/extend'), the resource ('rule'), and the precise scope ('one request variant from a captured entry'), making it clearly distinguishable from siblings like mock_create_from_entry, which focuses on a different mechanism.

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 extensive context on how to use the tool: it explains variant selection via match_body_fields, host_scope options, match_path patterns, mode differences, merge behavior, and status/delay overrides. It doesn't explicitly name alternatives or state 'when not to use', but it implies the use case (creating a rule from a captured entry) and provides enough guidance to select this tool for that purpose.

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 present, the description carries the full behavioral burden. It does disclose one meaningful behavior: fixture rules include the stored fixture in the result. However, it does not state that this is a read-only op, what happens for non-fixture rules, or what max_chars trims, leaving the behavioral picture only partially transparent.

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 states the core action first and appends the conditional caveat. No filler, no redundancy; every word 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 3-parameter tool with no annotations and a low-richness description, the definition is too thin: it offers no help choosing among the many mock_* and mock_rule_* siblings, no clarification of the extra relationship between rule and stored fixture, and no call of max_chars's effect. The output schema spares the need to explain return values, but the selection and param semantics gaps remain.

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 only 33%, so the description must compensate for rule_id and max_chars semantics — it does not. The description relies on the word 'fixture' to clarify rule_id only by implication and never explains that max_chars constrains the displayed output, leaving parameters substantially under-documented.

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 and resource ('Show one rule document') and adds a valuable distinguishing detail about fixture rules returning the stored fixture. The word 'one' signals a single-item getter against list-style siblings like mock_rule_list, but it never names those alternatives explicitly, so it stops short of full sibling differentiation.

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 guidance is given for when to call this tool instead of mock_rule_list, mock_get, or mock_rule_write. There is no mention of prerequisites such as needing a rule_id, how to obtain one, or when the fixture portion is relevant, so an agent gets no decision support.

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 behavioral burden. It discloses a notable behavior: invalid rule files are reported in `errors` and ignored by the dispatcher. This is valuable beyond the schema. It does not mention whether the operation is read-only, but 'List' implies a read operation and no mutation is suggested.

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. The core action and optional filter are front-loaded, and the error-handling behavior is appended in a second concise sentence. Every word 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 simple list tool with one optional parameter and an output schema, the description covers the key behavioral nuance (invalid rule files reported in errors). It doesn't describe the output structure, but the output schema exists and the description needn't explain return values. Minor gap: no explicit statement that this is a read-only operation, but 'List' makes that clear.

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 0%, so the description must compensate. It explains the `host` parameter's purpose ('optionally for one host'), which adds meaning beyond the bare schema. With only one parameter, this is sufficient; no other parameters need clarification.

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 ('List') and resource ('dispatcher routes and rules'), and adds an optional host filter. It is clear enough to distinguish from siblings like mock_rule_get (single rule) and mock_list (generic list), though it doesn't explicitly name a sibling.

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: call it to list routes/rules, optionally scoped to one host. It does not explicitly state when to prefer this over mock_list or mock_rule_get, nor does it mention any prerequisites. The optional host parameter gives some context but no explicit when/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?

The description discloses that the rule is archived (not deleted) and that its fixture is also archived, and that requests will pass through again. This is useful behavioral context. However, with no annotations provided, the description carries the full burden; it does not mention whether the operation is reversible, whether it requires the rule to exist, or what happens to the fixture data.

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 sentence, front-loaded with the action and effect. Every word earns its place; no filler or repetition of schema 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?

The tool has an output schema, so return values are covered. The description explains the core behavior and effect. However, with no annotations and a mutation-like operation, an agent would benefit from knowing whether archiving is reversible, whether the rule must exist, and how this differs from mock_rule_set_enabled. The description is adequate but not 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 50%: the 'host' parameter has a description, but 'rule_id' does not. The description adds context that the rule is archived, but it does not explain how host and rule_id together identify the rule, nor does it clarify the format of rule_id. The description partially compensates but leaves the rule_id parameter under-specified.

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 ('Archive') and resource ('one rule (and its fixture)'), and clearly explains the effect ('matching requests pass through again'). This distinguishes it from sibling tools like mock_remove and mock_rule_set_enabled, which have different semantics.

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 when to use it: when you want to stop a rule from matching and let requests pass through. However, it does not explicitly contrast with alternatives like mock_rule_set_enabled (which likely disables without archiving) or mock_remove (which may delete permanently). The context is clear but exclusions are not 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?

Annotations are absent, so the description carries the behavioral burden. It discloses the core side effect—toggling a rule's enabled state without deleting it—but does not mention whether the rule must exist, whether the change persists, or how errors are handled. Basic behavior is disclosed, but deeper effects remain opaque.

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 sentence with no filler, front-loading the key action and the non-deletion guarantee. Every word 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 simple three-parameter boolean setter, the description plus schema are nearly sufficient and an output schema exists. Missing usage guidance and behavioral details like persistence and error behavior prevent it from being fully self-contained.

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%, but the description partially compensates: 'enable or disable' maps to the enabled parameter and 'one rule' maps to rule_id. Host semantics are provided by the schema. This is helpful but still leaves rule_id undocumented beyond minimal inference.

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 and resource: 'Enable or disable' targets 'one rule' and adds 'without deleting it' to clarify non-destructive intent. It is clear, though it does not explicitly differentiate from the closely named sibling mock_set_enabled.

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 guidance is given about when to use this tool versus mock_rule_write, mock_rule_remove, or mock_set_enabled. Context is left entirely to inference from the sibling tool names.

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 must carry the full behavioral load. It correctly states the write (mutation) nature and the key constraint that fixture rules need fixture_json or fixture_text unless a fixture already exists. However, it does not disclose other important behaviors like overwrite semantics, error handling, or side effects.

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 compact and front-loaded with the action and alternative preference, followed by the shape and fixture notes. Every sentence adds value, though the shape definition could be slightly more structured, but overall it is efficient.

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 description covers the rule structure and fixture requirements, and an output schema exists for return values. It omits edge-case behaviors like whether the write overwrites existing rules, but given the 'advanced' label and the presence of an output schema, it is reasonably complete for an experienced agent.

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 schema has 0% description coverage and the 'rule' parameter is an unconstrained object (additionalProperties true), so the description is essential. It provides a detailed shape for the rule and explains when fixture_json and fixture_text are needed, significantly compensating for the sparse 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 clearly states the verb 'Write' and the resource 'rule document', and it explicitly recommends the alternative mock_rule_create_from_entry, which differentiates it from that sibling. The term 'directly' hints at a lower-level operation, but the core purpose is unambiguous.

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 explicitly names the preferred alternative (mock_rule_create_from_entry) and says to prefer it, providing clear 'when-not-to-use' guidance. However, it does not state explicit conditions under which this advanced tool should be chosen, leaving that partially to inference.

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 the side effect of disabling ('every request goes to real servers') and states that mock files are not deleted ('mock files stay on disk'). This is meaningful behavioral context beyond the 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 concise sentences with zero filler. The main action is front-loaded, and the clarifying consequence is placed immediately after, making the description easy to scan and act on.

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 single-boolean setter with no annotations and a trivial output schema, the description covers the essential behavior and the parameter meaning. It could slightly improve by explicitly routing to mock_rule_set_enabled for per-rule toggling, but the 'whole tool' phrasing makes that distinction reasonably clear.

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 schema only provides a boolean 'enabled' with 0% description coverage, so the description must clarify the parameter. It does so by mapping enabled on/off to real behavior: off means bypassing mocks and keeping files. The mapping is clear despite not explicitly saying 'true means enabled.'

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 ('Turn ... on or off') and a specific resource ('the whole Charles Map Local tool'), and the phrase 'whole' clearly distinguishes it from per-rule tools like mock_rule_set_enabled. An agent immediately knows what this tool controls.

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 clear context for when to use it: to toggle the entire Map Local tool, with the concrete consequence that off sends all requests to real servers while mock files remain on disk. It does not explicitly name alternatives or exclusion criteria, but the global scope is evident from the wording.

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?

Without annotations, the description fully discloses the tool's side effects: writes rules into Charles config, makes a backup first, and explicitly declares it never quits or starts Charles. It flags the critical constraint that apply=true only works while Charles is closed and explains the user's required manual steps. This is comprehensive behavioral transparency for a mutation 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?

The description is dense but well-structured: opens with the core purpose, explains the operational model (present/absent files), contrasts the apply modes, then lists side effects and prerequisites. Every sentence adds essential value, and the critical user action is saved for the end without wasting words. It is long but justified by the tool's complexity.

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?

Considering the presence of an output schema, the description covers all necessary operational aspects: setup steps, behavioral expectations, prerequisites for apply=true, and post-write actions. There is no obvious missing information an agent would need to safely and correctly invoke this tool. The output schema handles the return details, so the description's completeness is high.

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?

Overcomes the 50% schema coverage by providing rich context: 'host' is a bare hostname without scheme or port (complementing the schema's examples), and 'apply' is explained in detail—false gives manual steps, true writes to config with the caveat that Charles must be closed. This adds substantial meaning beyond the basic schema properties.

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 ('setup') and resource ('host'), precisely describing the one-time initialization action of creating a mock directory and Charles rules for Map Local and Rewrite. Distinguishes itself from siblings like mock_route_setup by emphasizing one-time host-level setup, making the tool's purpose clear and unambiguous.

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?

Provides explicit when-to-use: 'One-time setup per host' followed by 'After that, mocks are plain files...' which implies when not to use (only once). Also clearly states the difference between apply=false (manual steps) and apply=true (writes to config) and signals prerequisites (Charles must be closed) and sequence (user must save, quit, then start). This is exceptional guidance for an agent to decide when to invoke this tool.

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 of behavior disclosure. It says this writes a mock response but does not state what happens to existing mocks, whether this is a mutating/overwriting operation, or any side effects or destructive consequences. The mutual exclusivity of body/body_text is parameter-level guidance, not behavioral 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?

Three sentences, zero filler. The core action is front-loaded, parameter guidance is crisp (body vs body_text, not both), and the sibling-routing advice is placed last. Every sentence 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 write operation with no annotations and only half the params documented in the schema, the description is workable but incomplete. It gives a clear purpose and sibling preference, and an output schema exists so return values are covered, but it omits what happens when used against an existing mock or whether body/body_text may both be omitted. An agent could call this correctly most of the time but may need to inspect surroundings first.

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 50% (host, path) and body/body_text have no schema descriptions, so the description must compensate. It clarifies that body is a JSON value, body_text is raw text, and they should not be used together. This is valuable, but it stops short of saying whether one is required or what happens if both are provided.

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 and resource ('Write a mock response'), and the qualifier 'from scratch' clearly differentiates it from mock_create_from_entry. Even with many sibling tools, an agent can identify this tool's purpose immediately.

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 explicitly says to prefer mock_create_from_entry when a real response exists, telling agents when not to use this tool. It also gives concrete guidance on the body vs body_text choice, so the agent can select parameters correctly without further research.

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 it does well: it explicitly states the call does not consume messages, is safe to call repeatedly, and returns only compact summaries. That covers the most important behavioral traits an agent needs before invoking it.

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 front-loaded with the core behavior and every sentence adds value. It loses a point because the 'does not consume' point is made twice: 'does not consume the current increment' and 'does not consume items'.

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 peek tool with an output schema, the description covers the core behavior well, but it is not fully complete: it does not explain the meaning of capture_id, limit, or cursor beyond the cursor hint, and it does not state needed prerequisites such as an active capture. These gaps are moderate given the low parameter-level documentation in the schema.

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%, so the description must explain the parameters, but it mostly does not. The only partial light shed is on cursor through the wording 'does not advance the current cursor'; capture_id, limit, and full cursor semantics remain 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?

The description clearly states the verb and resource: it previews incremental traffic but does not advance the cursor. It also notes the return type is compact entry summaries, which helps distinguish it from read_live_capture and query_live_capture_entries. The final sentence explicitly routes structured uses to a sibling, reducing ambiguity.

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 directly says to use query_live_capture_entries for structured filtering and analysis, which is a useful when-to-use alternative. The 'does not consume' wording implicitly tells the agent to use this tool when it wants a side-effect-free preview, but it does not explicitly mention when to choose read_live_capture instead, so the when-not boundary is slightly incomplete.

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 behavioral disclosure burden and does so well: it states the tool does NOT advance the cursor, is safe to call repeatedly, defaults cursor=0 to scan from the beginning, and defines since_seconds as relative to query time. It does not cover every possible behavioral nuance, but the non-mutating, stateless nature is clearly conveyed.

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 longer than average but earns its length by front-loading the recommended usage and providing routing and cursor semantics. The get_traffic_entry_detail pointer appears twice in slightly different forms, which is a minor redundancy. Overall it remains well-structured and readable for the complexity involved.

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 description covers tool selection, cursor safety, and the recent-traffic shortcut, which is enough for basic correct use. However, with 25 parameters, no annotations, and no parameter-level descriptions in the schema, the high-level guidance is not sufficient for an agent to confidently use advanced filters or presets. An output schema exists, but that does not compensate for the underdocumented input semantics.

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 0%, so the description must compensate; it only explains cursor and since_seconds. The remaining 23 parameters, including preset, scan_limit, max_items, min_priority_score, and the JSON query filters, are left to be inferred from their names and enum values. This is a significant gap for a 25-parameter tool.

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 ('Analyze') and resource ('active live capture'), and explicitly frames the tool as the recommended way to inspect live/ongoing traffic. It clearly distinguishes itself from query_recorded_traffic and analyze_recorded_traffic, and positions itself as a summary layer before get_traffic_entry_detail. An agent can confidently tell what this tool is for and how it differs from 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?

The description gives explicit when-to-use guidance: prefer this for live/ongoing traffic, use recorded-analysis tools only when the user names a saved .chlsj recording. It also instructs to call this summary path before get_traffic_entry_detail, and recommends since_seconds for 'just now / recent' queries. This is exemplary routing guidance with named alternatives and conditions.

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 behavioral disclosure burden. It clearly discloses the key non-obvious trait: this tool never reads the live Charles session, only saved recordings. This is exactly the kind of safety-relevant behavior an agent needs. It does not describe failure modes or edge cases, but for a read-only query tool the most critical behavior is covered.

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 compact and front-loaded: the core action comes first, followed by the critical scope limitation, the usage condition, and the alternative tool. Every sentence earns its place with 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?

For a filtered read tool with an output schema, the description covers the essential invocation context: what it targets, when to use it, and what to use instead. The main gap is the unexplained boolean parameters, but that is already penalized under parameter semantics, and the output schema relieves the description of return-format duties.

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 schema covers 60% of parameters, but keep_request and keep_response are left with only titles and defaults, and the description adds no parameter-level guidance. An agent cannot tell what these booleans control or how they affect query output without additional inference.

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 and resource: "Query the latest saved recording." It explicitly labels the tool as HISTORY-PLANE and distinguishes it from live-traffic tools, so an agent can separate it from siblings like query_live_capture_entries without needing to open 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 gives an explicit condition: only use when the user references a saved recording (.chlsj file), and names the preferred alternative for live traffic (start_live_capture + query_live_capture_entries). This is direct, actionable 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?

No annotations are provided, so the description carries the burden. It discloses the consuming/advancing behavior, which is a key side effect, and the compact return format. It doesn't mention pagination limits or error conditions, but the core behavioral trait is well covered.

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 short sentences, each earning its place: what it does, what it returns, when to use an alternative, and the cursor side effect. Front-loaded with the core action.

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 the tool's simplicity and the presence of an output schema, the description covers the essential behavior and side effects. It could mention the limit parameter's default or the meaning of a null cursor, but the core usage is clear.

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 0%, so the description must compensate. It explains the cursor parameter's role (advancing cursor) and the limit's effect implicitly, but doesn't detail capture_id or the exact format of the cursor. The description adds some meaning beyond the schema but not full compensation.

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 reads incremental traffic and advances a cursor, with a specific verb ('Read') and resource ('live capture'). It also distinguishes itself from the sibling query_live_capture_entries by noting it returns compact summaries and consumes the increment.

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?

Explicitly says to use query_live_capture_entries for structured filtering instead, and explains the cursor behavior (repeated calls only return new items). This gives clear when-to-use and when-not-to-use 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 carries the full burden of behavioral disclosure. It indicates a destructive-then-restorative pattern ('Reset... and restore'), implying state reversion rather than clearing to factory defaults. However, it fails to specify what exactly gets reset (active captures? settings? sessions?) or whether unsaved work is permanently destroyed.

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 consists of a single, efficient sentence that frontloads the action verb 'Reset' and immediately qualifies the scope with 'restore the saved configuration.' Every word contributes to understanding the tool's dual-phase behavior without redundancy.

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?

While the description identifies the general operation, it lacks critical context for a state-resetting tool: it does not specify the scope of the reset, the source of the 'saved configuration,' or warn about destructive side effects. The existence of an output schema reduces the burden to explain return values, but the operational impact remains under-specified.

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 contains zero parameters, establishing a baseline score of 4 per evaluation rules. The description appropriately does not invent parameter semantics where none exist 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 uses specific verbs ('Reset' and 'restore') with the resource 'Charles environment' and distinguishes this state-management tool from traffic-analysis siblings like 'analyze_recorded_traffic' or 'query_live_capture_entries'. However, it assumes familiarity with what constitutes the 'Charles environment' without defining its scope.

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 provides no indication of when to invoke this tool versus alternatives, nor does it warn about potential data loss from resetting active sessions. There is no mention of prerequisites (e.g., whether a configuration must be saved first) or safe usage patterns.

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 full burden of disclosing side effects and operational traits. It mentions running a workflow but does not disclose that it may replay traffic (based on parameters like run_replay, replay_use_proxy) or any state changes. The description is too sparse to inform an agent of potential impacts.

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 concise at two sentences, but it is under-specified for a tool with 12 parameters and a complex workflow. It front-loads the action but omits necessary context, making it too short to be considered appropriately sized.

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 12 parameters, an output schema, and no annotations, the description is grossly incomplete. It does not explain what the workflow entails, what the summary/report contains, or how parameters influence behavior. The presence of an output schema does not compensate for the lack of operational guidance.

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 8% (only snapshot_format has a description). The description adds no information about any of the 12 parameters, such as limit, advance, run_replay, or path_keywords. It fails to compensate for the low schema coverage, leaving parameter meanings entirely to the agent's inference.

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 verb ('Run') and a resource ('task-oriented live API reverse-analysis workflow'), but 'task-oriented' is vague and does not specify what the task is. It also does not differentiate from sibling tools like reverse_analyze_live_login_flow or reverse_analyze_live_signature_flow, leaving ambiguity about its scope.

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 instruction 'Read summary/report first and expand evidence only as needed' gives a workflow hint but does not explain when to choose this tool over alternatives. No exclusions or alternative references are provided, so an agent cannot decide between this and similar analysis 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?

With no annotations, the description must carry the full burden of behavioral disclosure. It mentions a workflow and evidence expansion but does not state whether the operation is read-only, can affect live traffic, what it returns, or any side effects like replay or proxy usage. The behavior remains opaque.

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 two concise sentences with no filler. The purpose is front-loaded, and the usage hint is immediately actionable. It is efficient and well-structured, earning top marks for conciseness.

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 12 parameters, no annotations, and minimal schema descriptions, the description is severely incomplete. It lacks explanation of the workflow, expected inputs, outputs, or limitations, making it inadequate for an agent to use effectively.

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 only 8% (only snapshot_format has a description). The description does not elaborate on any of the 12 parameters, such as live_session_id, limit, advance, or run_replay. It adds no meaning beyond the schema, leaving agents without guidance on how to fill them correctly.

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 it runs a 'task-oriented live login/auth reverse-analysis workflow', specifying a specific verb (run), resource (live login/auth reverse-analysis workflow), and scope (new traffic). This distinguishes it from sibling tools like reverse_analyze_live_api_flow and reverse_analyze_live_signature_flow by focusing on login/auth.

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 provides a usage hint ('Read summary/report first and expand evidence only as needed') but does not explicitly state when to use this tool over alternatives like reverse_analyze_live_api_flow. The login/auth focus is implied but not contrasted with siblings, leaving selection criteria ambiguous.

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 full burden of behavioral disclosure. It only hints at a summary/report workflow and expanding evidence, but doesn't disclose side effects, safety, or how the workflow processes traffic. It's minimal and insufficient for an analysis 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?

The description is two sentences with no fluff, front-loading the purpose and giving a usage hint. It's structurally sound and concise, though extremely brief for a 13-parameter tool. It earns points for efficiency, not completeness.

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 the tool's complexity (13 params, no annotations, low schema coverage), the description is severely incomplete. It doesn't explain the workflow, parameter meanings, or when to use it, making it inadequate for correct 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 only 8%, so the description must compensate for 12 undocumented parameters. It provides no explanation of any parameters, leaving the agent to infer from names like 'limit', 'advance', 'run_replay', etc. This is a critical gap.

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 it runs a task-oriented live signature reverse-analysis workflow on new traffic, providing a verb and resource. It hints at a focus on signatures, which somewhat differentiates it from login/api flows, but it doesn't specify what the workflow does, what a signature is, or what the output is. The purpose is clear in a general sense but lacks precision.

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 only usage guidance is 'Read summary/report first and expand evidence only as needed,' which is about how to handle output, not when to choose this tool over siblings. No mention of alternatives like reverse_analyze_live_login_flow or conditions for selecting this workflow over others.

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 full burden of behavioral disclosure. It says 'Inspect' which implies a read-only operation, but it does not disclose what the returned status contains, whether the optional live_session_id changes the response shape, or whether any side effects occur. The description adds minimal behavioral context beyond the verb.

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 concise sentence that front-loads the primary purpose and appends the optional scope. No wasted words, though it could have used the space to add parameter semantics.

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 the tool has an output schema, the return value shape is covered elsewhere, but the description still lacks guidance on when to pass live_session_id, how this differs from charles_status, and what 'reverse live-session state' means. For a status-inspection tool with no annotations and one undocumented parameter, this is incomplete.

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 0%, so the description must compensate for the undocumented live_session_id parameter. The description mentions 'optional reverse live-session state' which loosely maps to the parameter, but it does not explain what values are valid, what the parameter controls, or how omitting it changes behavior. This is insufficient for a parameter with zero schema documentation.

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 ('Inspect') and resource ('Charles recording state'), and adds 'optional reverse live-session state' to distinguish it from the plain charles_status sibling. It is clear but does not explicitly name the sibling it differs from, so it loses one point.

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 the inspection counterpart to charles_status and the reverse_* live-session tools, but it does not explicitly say when to use this tool versus charles_status or reverse_peek_live_entries. The optional live_session_id hints at a conditional use case, but no explicit when/when-not guidance is 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?

With no annotations provided, the description carries the full burden of disclosing behavioral traits. It says 'Decode' but does not mention any potential side effects, required permissions, error behavior, or limitations on input size/format. The protobuf note is a start but insufficient for a tool that could fail if parameters are inconsistent.

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 sentence, which is concise and front-loaded with the core action. However, it is under-specified to the point of being terse, sacrificing helpfulness for brevity. While there is no wasted text, the minimalism reduces its 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?

The tool has 4 parameters (2 required) and an output schema, yet the description explains almost nothing about required inputs like 'entry_id' and 'side' or the expected output. Even though an output schema exists, parameter semantics are so poorly covered that the description is incomplete for a tool with this 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 description coverage is 0%, so the description must compensate for the four parameters. It only hints at 'descriptor' for protobuf, but does not explain the purpose of 'entry_id', 'side', 'message_type', or 'descriptor_path'. The agent has no meaningful guidance on what each parameter expects, making correct invocation unlikely without opening 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 clearly states the verb 'Decode' and the resource 'stored request/response body', which is specific and distinguishes it from sibling tools like 'reverse_get_entry_detail' that retrieve entries. It also mentions protobuf support, adding a relevant capability. It could be more explicit about what 'body' refers to, but the core purpose is unambiguous.

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 a conditional hint ('when a descriptor is provided') for protobuf decoding but provides no explicit guidance on when to use this tool versus alternatives. There is no mention of when not to use it or which sibling tools might be more appropriate for similar tasks, leaving the agent to infer the use case.

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 of behavioral disclosure. It indicates a read-only analysis operation (compare, rank), but it does not explicitly state that it has no side effects, nor does it mention any limitations, performance considerations, or input requirements. The description leaves the agent uncertain about whether this tool mutates state or has other behavioral traits.

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, concise sentence that front-loads the primary action and goal. It is appropriately sized for the tool's simplicity, though it could be slightly expanded to include usage context without becoming verbose. No wasted words, but it omits useful context.

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 an output schema, so return values are covered. However, the description does not clarify what entry_ids refer to (e.g., from a capture session) or what constitutes 'multiple requests'. It provides a basic understanding but lacks sufficient context for an agent to call it correctly without additional information, such as where the entry IDs come from or any prerequisites.

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 schema has zero description coverage for the sole parameter, entry_ids. The description only hints that these represent 'multiple requests' but does not explain what they are, their expected format, or any constraints. It adds minimal value beyond the parameter name, leaving the agent with insufficient guidance on how to populate the argument.

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 ('compare' and 'rank') on a specific resource ('multiple requests') with a clear goal ('fields that look signature-related'). It clearly conveys the tool's purpose, though it does not explicitly distinguish it from similar analysis tools like reverse_analyze_live_signature_flow. The purpose is understandable but could be sharper in differentiating from 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?

The description implies usage when you have multiple requests and want to identify signature fields, but it offers no explicit when-to-use guidance, no exclusions, and no mention of alternatives. An agent must infer the usage context from the tool name and sibling tools, which is insufficient for confident tool selection.

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 adds a useful prerequisite and clarifies single-entry scope, but it never explicitly states whether this is a read-only operation or whether any state is affected; the 'get' wording implies it but does not confirm it.

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 short sentences, with the core purpose first and the usage constraint second. There is no filler or irrelevant 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 one-parameter detail getter with an output schema, the description supplies the prerequisite and the non-bulk scope; nothing else is needed to invoke it correctly. The 'imported entry' phrasing also separates it from traffic/live-entry tools.

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 the description never mentions entry_id by name, format, or expected source. 'One imported entry' and 'candidate selection' imply the ID identifies a previously imported candidate, but this is too indirect to compensate for the schema gap.

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 ('Get'), a specific resource ('canonical detail view for one imported entry'), and explicitly scopes it to a single entry rather than bulk browsing. This clearly separates it from list-style siblings like reverse_query_entries.

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 after candidate selection' gives a clear trigger condition, and 'this is not a bulk-browsing endpoint' gives an explicit exclusion. It stops short of naming a specific alternative tool for bulk browsing, so the routing is strong but not fully explicit.

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 full burden of behavioral disclosure. It only states 'Import', implying mutation, but does not describe what happens to existing data, whether the operation is idempotent, authentication requirements, or any side effects. This is a significant gap for a mutation 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?

The description is a single sentence with no wasted words. It is concise, though it lacks any structured breakdown or clarification of key aspects.

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 that imports data and has three parameters (one required) plus an output schema, the description is too sparse. It does not explain the output, the meaning of parameters, or any behavioral context. Given no annotations, completeness is inadequate.

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 0%, so the description must explain the parameters. It only hints at the format (XML vs native) but does not explain the 'path' parameter or the meaning of 'source_kind'. The defaults are left unexplained, and the agent cannot infer parameter usage from the given text.

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 ('Import') and resource ('official Charles XML/native session') and names the target store ('canonical reverse-analysis store'). It clearly states what the tool does, but it does not differentiate from sibling tools or 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?

The description gives no guidance on when to use this tool versus alternatives. There is no mention of use cases, exclusions, or conditions under which this tool is preferred over other reverse-* or import-like 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 burden of behavioral disclosure. The description only says 'List imported captures' but does not disclose whether this is a read-only operation, whether it affects state, what the output format is, or any side effects. For a tool that lists data, the lack of explicit read-only confirmation and return format details is a 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?

The description is a single, concise sentence that front-loads the action and resource. It is appropriately sized for a simple list tool, with no wasted words. It could add a bit more context about the limit parameter or return format, but it is not overly verbose.

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 the tool's simplicity (one optional parameter, no nested objects, output schema exists), the description is mostly adequate. However, it lacks explicit behavioral context (e.g., read-only nature, ordering, or what 'imported captures' means in contrast to other capture types). The output schema exists, so return values are covered, but the description could better clarify the scope of 'imported captures'.

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 0%, so the description must compensate. The description does not mention the 'limit' parameter at all, but the parameter is simple (an integer with a default of 20) and its meaning is fairly inferable from the name 'limit'. The description adds no explicit meaning beyond the schema, so a baseline of 3 is appropriate given the simplicity of the single parameter.

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 ('List') and resource ('imported captures from the local SQLite store'), which clearly identifies the tool's function. It distinguishes itself from siblings like reverse_query_entries or list_recordings by specifying 'imported captures' and 'local SQLite store', though it doesn't explicitly name a sibling alternative.

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 context: it lists imported captures from the local SQLite store, which suggests it is for reviewing previously imported data. However, it does not explicitly state when to use this tool versus alternatives like reverse_query_entries or list_recordings, nor does it provide exclusions or conditions.

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 it only adds that findings are 'persisted' and that the operation is a list. It does not disclose filtering behavior, pagination, ordering, state expectations, or whether live analysis results are included. Some useful context is present, but it is minimal.

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 compact and front-loaded with the action, containing no filler. However, it is under-sized for a tool with two undocumented parameters and no annotations, so brevity comes at the cost of useful operational 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?

The description is too sparse to fully support correct invocation: it does not explain what a 'finding' is, how subject_id and subject_type alter the result, or how this tool relates to the replay and signature-candidate sibling tools. The output schema may cover return structure, but the invocation contract is still under-specified.

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 schema exposes subject_id and subject_type with no descriptions, and the tool description does not mention either parameter. An agent cannot infer how these parameters filter findings, what values are valid, or whether they are required. This is a significant gap given 0% schema description coverage.

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 action ('List') and resource ('persisted findings'), and scopes the tool to 'replay or signature-candidate analysis.' This makes the tool's place in the family reasonably clear, though it does not explicitly distinguish it from other analysis-related list/query 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?

The phrase 'from replay or signature-candidate analysis' implies this is the read-back step after those analyses have run, but there is no explicit when-to-use or when-not-to-use guidance. The large sibling list includes several analysis and query tools, and the description does not route the agent between them.

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. It states the key behavior (snapshot, inspect new entries, no advance) but omits important details: whether it requires an active capture, how 'new' is defined, what happens to the live cursor (explicitly no advance, but no mention of side effects like locking), or whether it consumes resources. It does not contradict annotations (none exist), but transparency is partial.

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