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

Annotations already flag destructive=true and idempotent=true, but the description adds the crucial blast-radius detail the annotations cannot convey: query changes EVERY matching issue in the project (up to 1000 per call) while issue_ids touches only the listed issues. This is exactly the kind of safety context that prevents an agent from accidentally mass-mutating a project.

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 tight sentences, front-loaded with purpose and scope, then the critical selection rule and its rationale. No filler, and every clause carries decision-relevant 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?

Covers purpose, scope, mutual exclusivity, and blast radius, which is strong for a 6-parameter destructive tool. The one gap is that no output schema exists and the description never indicates what the call returns (counts, affected IDs, or an empty acknowledgement), which an agent might need to confirm success.

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, but the description adds real meaning beyond the schema: the semantic difference between issue_ids (only those issues) and query (all matching issues), plus the 1000-per-call cap for query that the schema does not state. It does not elaborate on status/enum or assigned_to beyond what the schema already documents.

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 ("Bulk update issues in one project") and enumerates the exact operations available (resolve, ignore, unresolve, assign, mark seen). The word "bulk" plus the stated single-project scope clearly distinguishes it from the singular update_sentry_issue_status sibling without needing to name it.

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 defines the selection constraint: exactly one of issue_ids or query is required, and a call with neither is refused. It also explains why (Sentry would otherwise change every unresolved issue), which tells the agent when the tool will and will not execute.

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, idempotentHint=true, destructiveHint=false, and openWorldHint=true, so the safety profile is fully covered without the description. The description adds only the platform scope (iOS/macOS), disclosing nothing about auth requirements, whether it scans the whole project or a single event, or what a 'missing' result looks like.

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

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

A single front-loaded sentence with zero filler; the purpose and platform scope land immediately.

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

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

For a simple two-parameter read-only tool with no output schema and complete schema descriptions, this is close to sufficient. However, it omits whether the check covers the whole project or the optional single event, which is the key behavioral ambiguity for invoking 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 100% for both parameters, so the schema already explains project_slug and event_id. The description mentions no parameters at all and adds no meaning about how the optional event_id narrows the check versus a project-wide scan. 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?

States a specific verb ('Check') and resource ('debug symbols / dSYM files') plus the platform scope ('iOS/macOS crashes'). No sibling tool overlaps with this function, so no differentiation is needed, but the description stops short of stating exactly what the check returns or evaluates.

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

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

There is no explicit when-to-use or when-not-to-use guidance, no prerequisites, and no named alternatives. The agent must infer that this is for investigating symbolication problems during crash triage, which is reasonable but unstated.

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 the write profile (readOnlyHint=false, idempotentHint=false, destructiveHint=false, openWorldHint=true), so the safety picture is covered. The description usefully discloses the return value ('Returns the new comment id') in the absence of an output schema, but adds nothing about permissions 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?

Two short sentences, front-loaded with the action and followed by the return value. No filler, no 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?

For a two-parameter write tool with full schema coverage and annotations, the description plus the return-value note is nearly sufficient. It could be complete with a brief note on preconditions or the failure mode when the issue does not exist.

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

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

Schema description coverage is 100%, so both parameters (issue_id with short-ID example, comment_text) are already documented in the schema. The description adds no syntax or format meaning beyond that, which is the expected baseline when the schema does the work.

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 (add) and resource (comment on a Sentry issue), so an agent knows exactly what the tool does. No sibling tool performs commenting, so the purpose is unambiguous in context.

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 when-to-use, when-not-to-use, or alternative guidance. It does not mention raw_sentry_api as a fallback or note any preconditions (e.g. issue must exist) for commenting.

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 read-only, idempotent, non-destructive behavior, so the bar is lower. The description adds useful behavioral detail that binary attachments return metadata rather than content, and that grep_pattern can filter large logs.

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?

Very concise and front-loaded: the core read action comes first, followed by the binary limitation and the grep_pattern optimization. Every sentence carries useful 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?

Complete enough for a read-only attachment reader with full schema coverage and strong annotations. It explains the important binary-attachment edge case, though it does not describe the response shape for text attachments in detail.

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

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

Schema description coverage is 100%, so the schema already documents all five parameters, including grep_pattern and max_chars. The description reinforces grep_pattern's purpose for large logs but does not add substantial semantics 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: read the contents of a text attachment on an event. It also gives a concrete example and immediately clarifies the binary-attachment exclusion, which helps distinguish this from listing attachments.

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 usage context for large logs via grep_pattern and notes that binary attachments are not returned. It does not explicitly name list_event_attachments as the prerequisite/alternative, but the schema parameter descriptions already point there.

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 readOnly, idempotent, openWorld and non-destructive behavior, so the safety profile is covered. The description adds genuinely non-structured traits: it is scoped to the issue's latest event (not its full history) and enumerates the per-variant breakdown returned (contributes, hash, hint, summary). It says nothing about permissions or rate limits, which keeps it out of the top band.

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 purpose before the return-shape detail and the sibling pointer. The per-variant enumeration is dense but earns its place given there is no output schema; a slightly tighter phrasing could trim it further.

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 carries the burden of describing returns, and it does so at a useful level of detail (config plus per-variant contributes/hash/hint/summary). For a one-parameter read-only tool that is close to sufficient; missing only edge cases such as behavior when the issue has no events.

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

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

There is a single parameter with 100% schema description coverage, and the schema already explains that it accepts a numeric ID or short ID such as PROJ-1A2. The description adds no format, default, or validation detail beyond that, so the schema does the work and the baseline of 3 applies.

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

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

The description uses a specific verb+resource ('Explain why events are grouped into an issue') and adds the operating detail that it works off the issue's latest event. It explicitly distinguishes itself from the sibling get_issue_hashes by framing the relationship as a hash comparison, so an agent can differentiate without opening 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?

It states the operating context (takes the issue's latest event) and points at get_issue_hashes for hash comparison, which is a useful routing signal. It stops short of an explicit when-to-use/when-not rule or the condition that selects one tool over the other, so it is clear context rather than full guidance.

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

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

Annotations already declare readOnly/idempotent/non-destructive, so the safety profile is covered. The description adds real behavioral context beyond that: a fixed page size of 25 and the need to paginate via cursor, which tells the agent to expect multiple calls.

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

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

Three short sentences, each earning its place: purpose, motivation, and pagination mechanics, 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?

For a small two-parameter read tool with full schema coverage and no output schema, the description covers purpose and pagination adequately. Only a hint of what a hash looks like is missing, which is minor.

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 documented in the schema. The description's mention of cursor pagination mirrors the schema rather than adding new syntax or format detail; baseline 3 applies.

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

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

States a specific verb and resource ('fingerprint hashes for an issue') and frames the intent ('why events are grouped together'). It is distinguishable from siblings like get_issue_tags or get_stack_frames, though it doesn't explicitly contrast with 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 'useful for understanding why events are grouped together' gives an implied use case, but there is no explicit when-to-use/when-not guidance or named alternative tools. Usage is inferable rather than directed.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered without the description's help. The description adds only the semantic note that tags encode attributes like environment, OS, and user segment, which is modest added context for a read 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?

Two short sentences, with the core action front-loaded before the explanatory note about tags. It is efficient, though the second sentence is somewhat generic and could have been spent on disambiguating from the sibling tool instead.

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 read tool with annotations covering safety and no output schema, the description is adequate but leaves gaps: it does not describe the return shape (list of key/value tag pairs vs. keys only) or how it differs from get_issue_tag_values. Nothing an agent strictly needs is missing, but the sibling ambiguity is unresolved.

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

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

There is a single parameter with 100% schema description coverage, so the schema already explains that issue_id accepts a numeric ID or short ID. The description adds no format, syntax, or validation detail beyond that, making 3 the correct baseline.

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

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

The description states a specific verb and resource ('List all tags captured for an issue'), which is clear and unambiguous. However, it does not distinguish itself from the sibling tool get_issue_tag_values, which an agent could easily confuse with this one — both deal with issue tags.

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

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

No when-to-use guidance is given, and the closest alternative (get_issue_tag_values) is never named or contrasted. The sentence about tags identifying patterns hints at why tags matter but gives no condition for selecting this tool over its sibling.

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, idempotentHint=true, openWorldHint=true, and destructiveHint=false. The description adds useful behavioral context by saying it returns a frequency distribution of tag values, though it does not detail ordering, pagination beyond the schema limit, or exact response shape.

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 the core purpose front-loaded. There is no wasted language and the key constraint, a specific tag key, is stated immediately.

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

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

For a simple read-only distribution tool with full schema coverage and rich annotations, the description is nearly complete. The main minor gap is that it does not specify whether the response includes counts, percentages, or ordering.

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 issue_id, tag_key, and limit are already documented in the schema. The description reinforces the tag_key concept but adds no syntax or constraints beyond what the schema provides, making the baseline 3 appropriate.

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

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

States a specific verb and resource: getting tag value distribution for a specific tag key for an issue. It is clear enough to distinguish from listing tag keys, but it does not explicitly name or contrast with the sibling tool get_issue_tags.

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 about showing which values occur most frequently implies the use case, but there is no explicit guidance on when to choose this tool over alternatives such as get_issue_tags or other issue-related 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?

Annotations already declare read-only, idempotent, open-world, and non-destructive, so the safety profile is covered. The description adds what 'detailed information' includes (health stats, commits, authors), which is useful context beyond the annotations, but it does not discuss auth, rate limits, or error behavior.

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

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

A single, front-loaded sentence with no redundant words. It is appropriately sized for a simple read tool.

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 but rich annotations and full schema descriptions, the description provides enough content-level detail (health stats, commits, authors) to understand what is returned. It could mention the effect of the 'full' parameter more explicitly, but it is largely complete.

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

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

Schema description coverage is 100%: both 'version' and 'full' are fully documented in the schema. The description adds no parameter-specific syntax or behavior beyond what the schema provides, so baseline 3 applies.

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

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

States a specific verb (Get) and resource (release), and the singular 'a release' distinguishes it from the sibling list_releases, though that alternative is not explicitly named. It enumerates the returned content, making the purpose concrete.

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 implied context (fetching details for a known release) but does not say when to prefer this over list_releases or other issue tools, nor does it list prerequisites. No explicit 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?

Annotations already declare readOnlyHint, idempotentHint, non-destructive, and openWorld, so the safety profile is covered. The description contributes beyond that by warning about token limits on large events and recommending the limit parameter, but says nothing about return format, pagination interaction, or auth/permission needs.

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 front-loaded, followed by the practical limit warning. The ALL-CAPS 'IMPORTANT' is slightly noisy but the content 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?

With no output schema and full annotation coverage, the description is adequate but thin for a detail-retrieval tool: it does not describe the shape of returned event data or how entry_type filtering interacts with the limit/offset pagination fields.

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

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

Schema description coverage is 100%, so all five parameters are documented in the schema. The description adds a concrete example value (limit: 10) but no semantics beyond what the schema already provides; the baseline of 3 is appropriate.

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

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

States a specific verb (Retrieve) and resource (details for a specific event ID within a project), which is enough for an agent to distinguish it from list-style siblings like list_issue_events or get_issue_hashes. It does not explicitly name a sibling it differs from, so it falls short of a 5.

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

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

The description gives one actionable usage rule ('for large events, always use limit') but offers no when-to-use guidance relative to the many sibling retrieval tools (e.g., get_stack_frames, list_breadcrumbs, get_sentry_issue). Usage is implied rather than scoped.

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 this a safe, idempotent read; beyond that the description discloses what is and isn't returned (essential fields only, no stacktrace by default), what enabling include_latest_event adds (innermost frames per exception, message, recent breadcrumbs), and that responses are truncated. These are exactly the behavioral traits annotations cannot express.

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 identifier forms, then the return-value caveat and the flag that changes it. Dense but every clause carries information an agent needs before calling.

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 returns, and it does: essential fields only, conditional exception/message/breadcrumbs payload, and truncation behavior. Nothing needed to call this 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 every parameter including max_stack_frames, grep_pattern and include/exclude_fields is already documented. The description reinforces the include_latest_event coupling and truncation but adds no syntax or format details 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 (retrieve a Sentry issue) and enumerates the accepted identifier forms (numeric ID, short ID, URL). This clearly separates it from list-oriented siblings like list_sentry_issues and from get_sentry_event_details, which fetches events rather than the issue record.

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 makes the key choice explicit: the stacktrace is NOT returned unless include_latest_event is true, so an agent knows when to flip that flag. It does not, however, name an alternative tool (e.g. get_sentry_event_details or list_issue_events) for deeper event inspection, so routing guidance is implicit rather than complete.

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 annotations already declare read-only, idempotent, open-world, non-destructive behavior. The description adds little beyond the purpose statement: it does not explain frame ordering, missing debug symbols, filtering behavior, or other operational details.

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 short and front-loaded with the core action. The second sentence is slightly vague and adds little, but the overall size is appropriate.

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 and the schema plus annotations cover most invocation needs. However, with no output schema, the description gives only a high-level return description ("structured stack trace frames") and omits frame shape, ordering, or truncation behavior.

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 event_id, project_slug, max_frames, and in_app_only are already documented in the schema. The description does not add meaning beyond those parameter definitions, so the baseline of 3 applies.

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

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

The description states a specific verb and resource: extract stack trace frames from an event. It is clear what the tool does, but it does not differentiate from related event-detail tools such as get_sentry_event_details.

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 "Optimized for debugging" gives only vague context and does not say when to use this tool versus alternatives. There are no explicit exclusions, prerequisites, or sibling-tool routing guidance.

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

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

Annotations already declare readOnlyHint, idempotentHint and destructiveHint=false, so safety is covered. The description adds real behavioral context beyond them: the hard 90-day retention window, the requirement for performance/tracing data to be present, the tree-order-with-depth shape of results, and that errors unattached to any span are also returned. It stops short of describing truncation behavior or response volume limits, which the schema partly covers.

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 verb and resource, then a single dense parenthetical enumerating fields, then two short constraint sentences. No filler, no repetition of the title, and every clause carries information an agent needs.

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

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

With no output schema, the description carries the burden of explaining the return value, and it does so well: flat span list with fields, tree order plus depth, totals, and unattached errors. What it omits is pagination/truncation guidance tied to max_spans and whether the response indicates a truncated trace — a meaningful gap for a tool that can return up to 500 spans.

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

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

Schema description coverage is 100%, so both trace_id (32-char hex) and max_spans (1-500, default 100) are already documented, including the note that totals always cover the whole trace. The description's parenthetical field list mirrors the output rather than adding syntax or constraints for the inputs. 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?

Specific verb ('Get') plus resource ('a distributed trace') with an explicit enumeration of the returned span fields and the fact it is returned as a flat, tree-ordered list. An agent can immediately tell this is a read of one trace's span structure, distinct from the issue/event/release tools among the siblings.

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

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

It states a precondition ('Requires performance/tracing data') and a scope constraint ('Searches the last 90 days'), which are useful gating facts. However, it never says when to prefer this over an alternative (e.g. get_stack_frames or get_sentry_event_details) or what to do when the trace is older than 90 days or tracing is unavailable. Usage is implied rather than directed.

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

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so the safety profile is covered. The description adds useful context by enumerating which event types appear in the log, but says nothing about pagination behavior, ordering, or result size despite exposing a cursor.

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 purpose is front-loaded and the second sentence earns its place by listing the returned event categories. Slightly redundant with the resource name in the title, but tight overall.

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, three-parameter list tool with full schema coverage and rich annotations but no output schema, the description gives enough to call it correctly. The only mild gap is not clarifying its relationship to the other event-listing siblings.

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

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

Schema description coverage is 100%, so the schema already documents limit, cursor, and issue_id formats (including the PROJ-1A2 example). The description adds no parameter-level detail beyond that, which is the expected baseline when the schema does the heavy lifting.

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

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

States a specific verb and resource ('List activity log for an issue') and enumerates the content returned (comments, assignments, status changes). It is clear, but it does not explicitly distinguish itself from overlapping siblings such as list_issue_events or list_breadcrumbs, which also return per-issue event data.

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 scope implies when to use it (fetching an issue's activity trail), but there is no explicit when-to-use, no exclusions, and no pointer to alternatives like list_issue_events or list_breadcrumbs. Usage is inferable rather than 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 already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, openWorldHint=true, covering the safety profile. The description adds conceptual context (breadcrumbs = trail of preceding events) but omits pagination/return behavior. Minor internal tension: it says 'all breadcrumbs' while the schema caps results via limit (default 50, max 100).

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?

Single front-loaded sentence with no filler. It is appropriately sized, though slightly terse for a tool with a filtering parameter and pagination limit.

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 read-only list tool with full schema coverage and annotations handling safety, the description is adequate. It omits any mention of the result limit/pagination and how breadcrumbs are ordered, which an agent might need when interpreting truncated results.

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 type, limit, event_id, and project_slug fully. The description adds nothing parameter-specific, so baseline 3 applies.

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

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

States a specific verb ('Extract') and resource ('breadcrumbs from an event') with scope ('trail of events leading up to an error'). Clear enough to distinguish from siblings like get_stack_frames or get_sentry_event_details, though it doesn't explicitly name them.

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

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

No explicit when-to-use/when-not or alternatives. The phrase 'leading up to an error' implies investigation context, but there is no guidance on when to pick this over get_stack_frames or get_sentry_event_details for diagnosing an error.

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, destructiveHint=false and openWorldHint, so the safety profile is covered. The description adds only the project-wide search scope; it says nothing about result volume, ordering, or how the cursor/limit behave in practice.

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 zero filler, and the core scope statement is front-loaded before the use-case qualifier. Nothing here repeats the schema or wastes tokens.

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 list tool with no output schema, the description plus the fully documented schema cover what an agent needs to invoke it. Pagination mechanics and return shape are the only mild gaps, and the cursor parameter already signals pagination.

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% — full, limit, query, cursor and project_slug are all documented in the schema with defaults and bounds. The description adds no parameter meaning beyond that, so the baseline of 3 applies.

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

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

States a specific verb and resource ('List error events in a project') and adds a scope qualifier — searching across all events — that separates it from issue-scoped siblings like list_issue_events. It stops short of naming the sibling explicitly, so the differentiation is implied rather than crisp.

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 clause 'without knowing the issue ID' gives a concrete selection condition: reach for this tool when you lack an issue identifier and cannot use issue-scoped listing tools. No explicit alternative is named and no exclusions are stated, 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?

Annotations already declare readOnlyHint/idempotentHint/destructiveHint=false, so the safety profile is covered. The description adds real value beyond that: it implies this returns attachment metadata rather than content, and directs content retrieval to a different tool. It stops short of stating return format or pagination behavior, which keeps it at a 4.

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, zero filler, front-loaded with the resource and its concrete contents, followed by the selection rules and the related tool. 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 read-only list tool with full schema coverage and no output schema, the description covers purpose, mode selection, and the companion read tool. It is nearly complete; only minor items like pagination behavior are left to the schema's cursor field.

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

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

Schema description coverage is 100%, so the baseline is 3. The description adds scoping semantics beyond the schema by explaining the two mutually exclusive lookup modes (issue-wide vs single-event) and their parameter combinations, which clarifies intent rather than merely restating field docs.

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 ("List files attached to events") and immediately enumerates concrete attachment types (log files, minidumps, screenshots, view hierarchies), which disambiguates it from generic event/issue listers. An agent can distinguish it from siblings like get_event_attachment without opening 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?

Gives explicit routing: use issue_id to get every attachment on an issue, or project_slug + event_id for a single event. It also names the follow-up tool and when to use it ("Read text attachments with get_event_attachment"), making the list-then-read workflow unambiguous.

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 read-only, idempotent, non-destructive, and open-world behavior, so the safety profile is covered. The description adds usage context about occurrences over time but does not disclose additional behavioral details beyond what annotations and the schema provide.

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, front-loaded with the core action and followed by a concise usage note. There is no wasted text.

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

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

For a read-only listing tool with fully described parameters and clear annotations, the description is largely complete. It could mention pagination or how full event details differ, but the schema already covers those parameters.

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 already documented. The description adds no parameter-specific meaning beyond the schema baseline, so a 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?

States a specific verb and resource ("List all events") scoped to a specific issue, which distinguishes it from issue-listing tools. It does not explicitly differentiate itself from the sibling list_error_events or get_sentry_event_details, so sibling differentiation is incomplete.

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 second sentence gives clear usage context: viewing all occurrences of an error over time. It does not state when not to use it or name alternatives such as list_error_events or get_sentry_event_details.

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 readOnly, idempotent, open-world and non-destructive, so the safety profile is covered. The description adds the Sentry-query capability but says nothing about return shape, pagination behavior via cursor, or default scope when query is empty, which the missing output schema leaves unaddressed.

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 no filler, and the core purpose is front-loaded before the sibling comparison. Efficient, though the second sentence could carry one more useful clause without bloat.

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 five-parameter search tool with no output schema and no required parameters, the description covers purpose and sibling routing but leaves the default behavior with an empty query, the nature of the returned list, and pagination flow unexplained. Adequate but with clear gaps.

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

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

Schema coverage is 100%, so full/full-object vs. compact triage, sort enum, limit bounds and cursor are all documented in the schema. The description's query example merely duplicates the schema's example, adding no new parameter meaning; 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+resource (list issues) and names the confusable sibling list_sentry_issues, clarifying that this one is not project-scoped. The exact scope (org-wide vs. a default project) is left implicit, keeping it short of a 5.

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

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

Gives a usable selection axis by calling itself 'more powerful than list_sentry_issues which is project-scoped', implying this is the tool for cross-project / query-driven search. It stops short of an explicit when-to-use rule (e.g., what to do when query is omitted) or a when-not-to-use exclusion.

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, openWorldHint and destructiveHint=false, so the safety profile is covered. The description adds only conceptual framing and says nothing about pagination behavior (the cursor param), result caps, or default windowing that an agent would need to know.

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, front-loaded sentences with no filler; the core action leads and the definition follows. It is efficient, though the second sentence is informational rather than actionable.

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?

Parameters are fully described by the schema and there is no output schema to explain, but with 27 siblings including get_release_details the description omits any routing guidance, leaving completeness merely adequate for a list tool.

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

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

Schema description coverage is 100%, so all five parameters (date, sort, limit, query, cursor) are fully documented in the schema itself. The description provides no additional parameter meaning, 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 ('List releases in the organization') and adds a useful one-line domain framing about what a release represents. However, it never distinguishes itself from the sibling get_release_details, which an agent could easily confuse with this listing tool.

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

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

There is no statement of when to use this tool versus get_release_details or raw_sentry_api, nor any conditions, prerequisites, or exclusions. Usage must be inferred entirely from the name and the vague 'in the organization' scope.

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 destructiveHint=false, so safety is covered. The description adds that pagination is supported, but doesn't explain return shape or the full vs compact tradeoff (left to 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 short sentences, front-loaded with the core action and scoping, with minimal waste. Slightly terse given the ambiguity with a sibling tool, but 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 schema is fully described and annotations cover the safety profile, so the mechanical calling information is complete. However, the overlap with sibling list_issues is unaddressed, leaving a meaningful selection gap for the 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 coverage is 100%, so all six parameters are already documented in the schema; the description only echoes query/status and pagination. Baseline 3 is appropriate when the schema does the heavy lifting.

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

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

The description states a clear verb (list) and resource (issues) scoped to a specific project, with optional filtering. It does not, however, distinguish itself from the sibling tool list_issues, which an agent could easily confuse it with.

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 mentions that filtering by query or status is optional and that pagination is supported, which implies usage, but gives no guidance on when to prefer this over list_issues or other siblings, and no exclusions or prerequisites.

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 destructiveHint=false, so safety is covered. The description adds genuine behavioral context the annotations lack: it discloses that the result may carry next_cursor and how to consume it, and that returned project objects are trimmed to 'essential fields only'.

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, the resource and scope are front-loaded, and the pagination instruction follows immediately. No filler or restated boilerplate.

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 usefully covers the one return detail that matters for correct invocation: the next_cursor pagination token. It is complete enough for a single-optional-param read tool, though it says nothing about ordering, filters, or what happens when no projects exist.

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 already documents cursor as 'next_cursor from a previous call', which the description essentially repeats. Baseline 3 applies; the description adds the loop-level framing but no 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 ('List projects in the configured Sentry organization') and adds a scoping qualifier ('essential fields only'). The resource is clearly distinct from siblings like list_teams or list_releases, 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 context is implied (call it when you need the organization's project list), and it does explain the pagination loop for the cursor. However, there is no explicit when-to-use vs alternatives guidance and no stated conditions or prerequisites.

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, destructiveHint=false and openWorldHint, so the safety profile is fully covered structurally. The description adds only the organizational scope ('all teams in the organization'); it says nothing about pagination, result size, or ordering.

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

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

A single front-loaded sentence with no filler; the scope qualifier is stated immediately and nothing is wasted.

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

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

For a no-parameter, read-only list tool with rich annotations and no output schema, the definition covers what an agent needs to invoke it. Only return-shape details (pagination, result volume) are absent, which is a minor gap.

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

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

The tool takes zero parameters, so the baseline is 4. There is no parameter semantics to add 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 (List) and resource (teams) with a scope qualifier ('in the organization'). It is immediately distinguishable from siblings like list_sentry_projects or list_issues, though it does not explicitly contrast itself with any of 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?

There is no when-to-use guidance, no prerequisites, and no mention of alternatives or related tools. For a trivial enumerator this is tolerable, but the description provides zero routing information.

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, openWorldHint and destructiveHint=false, so the safety profile is covered. The description adds meaningful behavioral context beyond that: reporter emails are redacted/omitted, and results can be scoped to a single issue or an entire project.

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 tightly written sentences with no filler. The core purpose is front-loaded and the mutual-exclusion constraint follows immediately, so nothing needs to be skimmed for.

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 list tool with no output schema, the description covers purpose, scoping, the XOR constraint, and a notable privacy behavior (emails omitted). It could mention pagination/return shape explicitly, but the cursor parameter in the schema largely covers that.

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, but the description adds real semantics the schema lacks: issue_id and project_slug are mutually exclusive and exactly one must be supplied. It also reinforces the scoping effect of project_slug (all feedback in the project).

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 ("List user feedback") and disambiguates with a parenthetical explaining what feedback actually is (what end users wrote when reporting a crash). The scope (an issue or a whole project) is stated, so an agent can immediately tell what this returns versus issue/event listing 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 an explicit invocation rule: "Pass exactly one of issue_id or project_slug," which steers the agent to valid usage. It does not name alternatives or state when-not to use it (e.g. versus list_issue_events), so it falls short of full routing guidance.

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

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

Annotations only declare destructive/non-idempotent/open-world; the description adds the operationally critical facts that Sentry picks the surviving parent itself (earliest first-seen, not necessarily issue_id), that the others become children, and that the merge completes asynchronously. These are non-obvious behaviors an agent could not infer from the schema or hints.

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 tight sentences, no redundancy. Scope restrictions come first, then the behavior of the merge, then the precondition — a sensible priority order for a destructive operation.

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 only two well-documented parameters, no output schema, and a destructive hint, the description covers everything an agent needs: eligibility restrictions, async completion, parent-selection semantics, and the precondition. No meaningful 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 coverage is 100%, so baseline is 3, but the description still adds real meaning: it clarifies that issue_id is not guaranteed to be the surviving parent, which reframes what the parameter actually controls. It does not restate formats already in the schema, keeping the addition purely additive.

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 ('merge issues of the same project into one') and immediately narrows scope with two constraints: error issues only, cross-project merges refused. This distinguishes it cleanly from siblings like bulk_update_issues, which mutate status rather than consolidate issues.

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 confirming the issues share a root cause' gives a clear precondition for invocation. It stops short of naming alternatives or stating when NOT to use it, so it is one step below fully explicit routing guidance.

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

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

Annotations already declare destructiveHint=true, openWorldHint=true and readOnlyHint=false, so safety is partly covered. The description adds real behavioral value beyond that: it warns that event endpoints can return 100K+ tokens and that responses are unfiltered. It stops short of covering auth requirements or confirming DELETE/PUT 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?

Three tight sentences, front-loaded with purpose then the token warning, with zero filler. Every sentence 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?

For an open-world, potentially destructive raw API tool with no output schema, the definition covers purpose, the unfiltered-response caveat, and the token-blowup risk. It omits mutation/permission caveats (DELETE/POST effects), leaving a small gap for a dangerous tool.

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

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

Schema description coverage is 100%, so all five parameters (including method enum and the endpoint path format) are already documented. The description reinforces grep_pattern's importance for events, but this largely repeats the schema's own 'CRITICAL for event endpoints' note, so it adds little beyond the baseline.

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

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

The description states a specific verb and resource ('Make a raw API call to any Sentry endpoint') and adds the key qualifier 'Returns unfiltered JSON', which distinguishes this escape-hatch tool from the many specialized siblings like list_sentry_issues or get_sentry_event_details. An agent can tell exactly what this does without opening 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 one concrete conditional ('Use grep_pattern for events') but never routes the agent between this generic tool and the specialized siblings, nor says when the raw escape hatch is preferred over them. Usage is implied rather than 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 already declare readOnlyHint=false, idempotentHint=true, destructiveHint=false, and openWorldHint=true, so the safety profile is covered. The description adds the return shape (issue id, short ID, title, new status), which is genuinely useful, but says nothing about permissions or side effects beyond what annotations provide.

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 zero waste; the action is front-loaded and the return info follows. Nothing could be trimmed without losing meaning.

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 naming the returned fields compensates usefully, and the simple two-parameter shape is fully covered by the schema. The only gap is the absence of routing guidance against the bulk sibling.

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

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

Schema description coverage is 100%, so both parameters and the status enum are fully documented in the schema. The description adds no format or syntax detail beyond it, so the baseline of 3 applies.

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

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

States a specific verb and resource: 'Update the status of a Sentry issue.' An agent immediately knows the operation. It does not differentiate from the sibling bulk_update_issues, so it stops short of a 5.

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

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

No when-to-use guidance and no mention of alternatives. With bulk_update_issues and merge_issues among the siblings, the description gives no signal about when this single-issue variant is preferred over the bulk one.

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 readOnly, idempotent, non-destructive, open-world, so safety is covered. The description adds real diagnostic context beyond that: it is a preflight/failure-triage tool and it reports scope-derived tool availability, which an agent could not infer from the annotation set. It does not describe the response shape, but with no output schema this is a modest omission rather than a blocker.

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, zero filler. What it reports comes first, the actionable routing instruction ('call this first on 401/403') is last and easy to scan, so the agent gets payoff and trigger in one pass.

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-argument diagnostic tool with full annotation coverage, the description supplies everything an agent needs: what it inspects, why the result matters (which tools are ruled out by scopes), and when to invoke it. No output schema exists, yet the return contents are summarized in prose, so nothing essential 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?

Zero parameters, so there is nothing for the description to disambiguate; baseline 4 applies. The description correctly implies no input is needed by framing the tool as a pure connection inspection.

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 (check) and resource (the Sentry connection/token), then enumerates the exact facts returned: user identity, token scopes, organization reachability, and which tools the scopes rule out. This is unmistakably the diagnostic/identity tool and is differentiable from every sibling, which are all data-fetching or mutation 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?

Gives an explicit trigger condition: 'Call this first when other tools fail with 401/403,' which is exactly the situation an agent needs routing for. It stops short of stating when NOT to call it (e.g. whether it is worth calling preemptively before a long workflow), leaving a small gap, but the primary usage signal is clear.

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