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

Annotations already declare readOnlyHint, idempotentHint, and openWorldHint=false. The description adds non-obvious behavioral details: comparison direction is always older-to-newer, key order/formatting/per-delivery headers are ignored, and omitting `b` compares against the previous same-type event on the same endpoint.

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

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

Front-loaded and compact: the first sentence defines the operation, later sentences cover use cases, default behavior, comparison direction, and ignored differences. Every clause 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 three-parameter read-only comparison tool with rich schema descriptions and annotations, the description covers what is compared, how defaults work, comparison direction, and noise exclusions. Although no output schema exists, the field-by-field diff concept is clear enough 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 100%, and the schema itself documents event forms for `a`, the default for `b`, and the `include_headers` boolean. The description reiterates the `b` default and header comparison but adds little new per-parameter meaning beyond the high-coverage schema.

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

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

States a specific verb-resource pair: shows what differs between two captured webhooks, field by field using JSON paths, plus header differences. This clearly distinguishes it from siblings like get_event, list_events, and replay_event.

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 concrete usage scenarios such as debugging a worked-vs-failed event or spotting provider payload changes, and explains the default comparison when `b` is omitted. It does not explicitly name alternatives or when-not-to-use cases, 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?

Adds real behavior beyond the annotations: same-name calls return the existing endpoint rather than duplicating, plan caps apply, and secrets are deliberately kept out of the conversation. The name-based dedupe sits in mild tension with idempotentHint=false, but it describes a distinct dedupe rule rather than contradicting the hint, so no contradiction is flagged.

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, front-loaded with the action and return value, then dedupe behavior, limits, and the secret exclusion. Every sentence carries information an agent would otherwise have to guess.

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 three-parameter creation tool with no output schema, the description covers the return value, duplicate handling, quota constraints, and the deliberate omission of secrets. Nothing an agent needs to call it correctly is missing.

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

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

Schema description coverage is 100%, so the schema already documents name, relay_to, and signature_scheme. The description adds only the negative fact that no signing-secret parameter exists, which is useful but does not deepen per-parameter meaning beyond the schema.

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

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

States a specific verb and resource ("Creates a new catch URL (endpoint) in the current workspace") and even names the return value (the URL to paste into the provider's webhook settings). No sibling tool creates endpoints, so the definition is unambiguous against list_endpoints, run_scenario, and the rest.

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

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

Gives clear context for when to call it (setting up a provider webhook) and an explicit exclusion: it does not take a signing secret, which is added in the dashboard instead. It also warns about plan limits (Free has 3 endpoints). It stops short of naming an alternative tool, but no sibling performs this action.

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

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

Annotations already declare readOnlyHint, idempotentHint, and openWorldHint false. The description adds substantive behavior beyond that: which provider schemes it detects, the likely causes it diagnoses, and that a candidate secret can be tested without saving 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 dense sentences with no wasted wording. The core debugging purpose comes first, followed by the saved-versus-candidate secret distinction.

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

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

For a read-only debugging tool with full parameter documentation and no output schema, the definition gives enough context to invoke it confidently. It could say more about the returned diagnostic format, but the listed failure causes cover the essential expectation.

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

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

Schema description coverage is 100%, so the input schema already documents both parameters thoroughly. The description reinforces that `secret` is a candidate tested without saving, but adds little syntax or format meaning beyond the schema.

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

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

States a specific verb and resource: explains why a webhook signature verified or failed. It names provider schemes and concrete failure causes, which makes the tool clearly distinct from siblings like replay_event or compare_events.

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 troubleshooting context is clear: use this when a signature verified or failed and you need to know why. It does not explicitly name alternatives or exclusions, but the debugging purpose is strongly implied by the failure-cause list.

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

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

Annotations already declare readOnlyHint and idempotentHint, but the description adds genuinely new behavior: it writes nothing to disk, returns file contents with suggested names, and requires the caller to persist them. Because there is no output schema, the note that the response is unsaved file contents plus a signature-scheme hint is the key information an agent needs before acting. It stops short of describing error behavior for a bad event_id.

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

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

Front-loaded with the core transformation, then deliverables, then language variants, then the no-side-effect caveat. Every sentence carries content, though the closing signature-scheme sentence is slightly bolted on and could be folded into the deliverables list.

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

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

With no output schema and four parameters at full coverage, the description adequately covers what comes back (file contents with suggested names) and the critical constraint that nothing is written. Remaining gaps, such as failure modes on an unresolvable event_id or size limits on generated output, are minor for a read-only code generator.

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

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

Schema coverage is 100%, so a 3 would be the floor, but the description goes further by explaining what each language actually yields (typescript with Jest/Vitest, python dataclasses with pytest, php DTO with Laravel test, go structs with no test). That per-value meaning is not derivable from the bare enum and directly affects the caller's choice.

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 ('turns a real captured webhook into code') and immediately enumerates the concrete artifacts produced: typed models, a fixture file, and a test. The per-language breakdown makes it unmistakable against siblings like get_event, replay_event, or list_events, which deal in event data rather than generated code.

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 context is clear: you use this after having a captured event, and the enum of languages signals the required inputs. It implicitly routes the agent to list_events for the event_id format. However, it never says when NOT to use it or names a sibling alternative explicitly, so it falls short of a full when/when-not treatment.

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

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

Annotations already declare readOnlyHint and openWorldHint=false, so the description's added value is the disclosure of truncation behavior ('Long bodies are cut at max_body_chars'), which tells the agent results may be partial. It does not cover error behavior for an unknown event id or what 'signature status' concretely reports.

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 tight sentences with zero filler; the returned-field list comes first and the truncation caveat is placed last where it belongs as a qualifier.

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

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

With no output schema and only two parameters, the description adequately signals the shape of the response and the one lossy behavior. Missing only edge-case behavior such as a not-found event or the meaning of signature status.

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

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

Schema coverage is 100%, so the schema already documents both parameters in detail, including the accepted event_id forms. The description reinforces the truncation semantics of max_body_chars but adds no new syntax or constraints beyond the schema — baseline 3.

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

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

Specific verb ('Reads') plus resource ('one captured webhook') and an enumeration of what is returned: method, headers, query string, body, signature status. The singular 'one' implicitly separates it from list_events, though no sibling is named explicitly.

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

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

Usage is only implied by the word 'Reads one' — an agent can infer this is for inspecting a single captured event after finding its id. There is no explicit when-to-use, no pointer to list_events for discovery, and no guidance on when compare_events or replay_event would be preferred.

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

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety is covered. The description adds genuinely useful behavior beyond that: replays from both the dashboard and `slinghook listen` are included, the verdict is computed against the prior attempt to the same URL, and both response bodies are only returned on Pro and above — a tier-gating detail an agent cannot get from structured fields.

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, front-loaded with the core purpose and verdict semantics, with no filler. Slightly dense with parenthetical asides, but every clause carries information.

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

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

With no output schema, the description does the necessary work of explaining what comes back: the replay history, the four verdict values, the comparison baseline, and the conditional response bodies. Only the shape of the history list itself is left unspecified, which is a minor gap for a read-only 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 coverage is 100%, so both parameters are already fully documented, including the flexible event_id formats and replay_id defaulting to latest. The description only restates that replay_id selects a specific attempt; it adds no syntax or format detail beyond the schema, so the baseline 3 applies.

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

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

States a specific verb and resource ('Shows the replay history of one event') plus the verdict for the latest replay, and enumerates the verdict values (fixed, regressed, still_failing, still_passing). This clearly separates it from siblings like replay_event (which creates a replay) and compare_events.

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

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

Usage is only implied: an agent can infer this is the tool to call after a replay to check whether a fix worked, but the description never says when to use it versus replay_event or compare_events, nor any prerequisites such as needing an existing replay.

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

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds useful scope information (results are limited to the current SlingHook workspace) but says nothing about ordering, pagination, or what happens with an empty workspace, so it only modestly exceeds the annotations.

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 no filler: the first states what is returned, the second states when to reach for it. The key information is front-loaded and nothing is repeated from the title.

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 zero-parameter read tool with annotations covering the safety profile, the description supplies the essentials: workspace scope, the identity of endpoints as catch URLs, their relay targets, and its role as an entry point. The only real gap is return shape/pagination detail, which is minor for a simple list call with no output 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?

The tool takes zero parameters, so the baseline is 4. The description correctly frames the call as scope-free (workspace-determined) rather than implying any filtering input the agent might look for.

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 ("Lists the catch URLs (endpoints)") and immediately disambiguates the term by explaining what an endpoint is and that its relay destination is included. This makes it clearly distinct from siblings such as list_events, get_event, or create_endpoint.

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 sentence "Start here to find the endpoint a webhook was sent to" gives concrete entry-point guidance and implies this should precede event-level lookups like list_events or get_event. It stops short of naming those alternatives or stating exclusions, so it is clear context rather than explicit 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?

Annotations already establish a safe read (readOnlyHint, openWorldHint=false), but the description adds real substance: summaries are body-less, results are ordered newest-first, the non-paged read caps at 50 on every plan, and whole-history search requires Pro. It does not mention pagination cursor semantics beyond before_id or result envelope details, but coverage is strong for a list 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?

Three tightly packed sentences: what it returns, where to go for the full event, then the two modes and their plan constraints. No filler and the core behavior leads.

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

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

With no output schema, the description correctly spends its words on the returned summary fields and the body exclusion, which an agent needs to know. Plan limits, ordering, and the alternate tool are all covered, leaving no material 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 coverage is 100%, so the baseline is 3; the description earns more by explaining the coupling between the absence/presence of query and before_id and which data set (newest vs. retained history) is scanned. It repeats the Pro gating already present in the schema descriptions, so it stops short of a 5.

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 ('Lists webhooks captured on an endpoint') plus scope ('newest first') and the exact shape of what comes back (number, time, method, event type, signature status, no bodies). It also distinguishes itself from get_event, so an agent can pick it without opening a schema.

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

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

Explicitly routes the agent to get_event for a full single event, and explains that omitting query/before_id gives the newest events while supplying them searches retained history. It even names the plan gating each mode, which is the main decision factor for an agent choosing a call strategy.

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

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety is covered. The description adds genuine context beyond that—scenarios are ordered event sequences and are authored in the dashboard, so they cannot be created through this API—but it says nothing about pagination, ordering of the returned list, or behavior for an unknown endpoint slug.

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

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

Two sentences, front-loaded with the action, and every clause earns its place—the parenthetical example makes 'scenario' concrete, and the dashboard note is a real scope signal rather than 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?

There is no output schema, so the description carries the burden of describing the return value. It conveys that a list of scenarios comes back but not whether each entry includes an identifier (needed to call run_scenario) or a name/count, which is the key detail for the natural follow-up call. Otherwise adequate for a single-parameter read 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 coverage is 100% and the endpoint parameter's schema text already specifies UUID, catch URL, and reserved slug formats. The description only echoes 'on an endpoint' without adding format or resolution details, so the schema does the heavy lifting and the baseline 3 applies.

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

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

States a specific verb and resource ('Lists the saved scenarios on an endpoint') and goes further by defining what a scenario is: an ordered set of captured events that run_scenario replays. That definition separates it cleanly from siblings like run_scenario (which replays) and list_events (which returns raw events) without the agent needing to open any schema.

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

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

Usage is only implied: by describing scenarios as the thing run_scenario replays, the description hints this is the discovery step before running one, and 'built in the dashboard' implies there is no create_scenario equivalent. It never explicitly states when to call this versus list_events or what to do with the result, so the agent must infer the 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?

Annotations already flag destructive, open-world and non-idempotent behavior, and the description adds substantive context on top: the original method/headers/body are preserved, the attempt is written to dashboard replay history, and the returned verdict is defined against the prior attempt to the same URL (fixed, regressed, still_failing, still_passing). The explicit warning that it can change state in the receiving app reinforces rather than repeats the annotations.

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 core action and its target come first, followed by side effects and return semantics, so it is well front-loaded. Four sentences is a reasonable length for the behavioral payload, though the parenthetical example URL slightly duplicates the target_url example in the schema.

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

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

With no output schema and a destructive, open-world delivery, the description does the heavy lifting by naming the four verdict outcomes and the history recording. It stops short of saying what else is returned about the delivery (status code, response body), which matters for diagnosing a failing local handler.

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

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

Schema description coverage is 100%, so the schema already explains both event_id forms and target_url. The description contributes nothing parameter-specific beyond the generic 'a URL from this machine' phrasing, so the baseline 3 applies.

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

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

The description uses a specific verb+resource ('Re-sends a captured webhook to a URL') and pins the scope to deliveries made from this machine with a concrete example URL. It implicitly separates itself from retrieval-style siblings by emphasizing that a real delivery is made, but it never names an alternative tool, so the differentiation is inferential rather than explicit.

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

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

It gives a clear when-to-use rationale ('so signature checks run for real') plus a practical caveat that a correctly configured handler passes an invalid-signature event by rejecting it with 4xx. It does not name when NOT to use it or point to siblings such as get_replay_result or debug_signature, which an agent choosing between replay-style tools would want.

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?

Beyond annotations that already flag destructive and open-world behavior, the description discloses that each step is a real webhook delivery recorded in replay history and can change state in the receiving app. It also clarifies timing behavior: steps run back to back unless keep_timing is set, with gaps capped at 5 seconds.

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 action and scope, then adds usage, timing, and side-effect context without filler. Every sentence contributes operational detail an agent needs.

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

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

For a multi-step, state-changing tool with no output schema, the description covers what is returned (status, pass/fail, verdict against prior replay), timing behavior, and real side effects. The remaining parameter details are fully covered by 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 100%, so all four parameters are documented in the schema. The description reinforces keep_timing semantics and target_url behavior but adds little beyond the schema and does not mention stop_on_failure.

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: it replays every event of a saved scenario in order to a target URL and reports per-step results. It also contrasts the scope with single-event replay, so an agent can distinguish it from replay_event without inspecting the schema.

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

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

It gives a clear usage context: use after a fix to prove a whole flow works, not just one event. The alternative single-event tool is implied rather than named, so the routing signal 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.