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

Annotations already declare destructive and idempotent behavior, so the description does not need to repeat those. It adds the useful behavioral fact that the token is consumed and must be fresh, and that the action was previously previewed, but it does not describe failure behavior or post-consumption consequences.

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. It conveys the action, the key precondition, and the source of the action in just nine words, which is appropriately concise for a simple two-parameter 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?

The tool has only two primitive string parameters, no output schema, and annotations already cover destructive/idempotent/open-world aspects. The description establishes the critical precondition (fresh token) and the effect (perform previewed action), which is sufficient for this low-complexity commit tool, though it could still mention what happens if the token is stale.

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

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

Schema description coverage is 0%, so the tool description must compensate for undocumented parameters. It only loosely clarifies the token as an 'approval token' and provides no additional meaning for approval_id or how the two fields relate, leaving a real gap.

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

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

The description clearly says the tool consumes an approval token and executes the action that was previewed, which identifies a specific commit/execute role in an approval flow. It does not explicitly name a sibling alternative, but the distinction from the many propose/draft siblings is implicit and adequate.

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 'consume a fresh approval token' implies this is the step to run after an approval has been obtained, and this is useful guidance. However, the description does not explicitly say when not to use it or name alternatives such as proposal or draft tools, leaving some inference required.

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, so the description does not need to restate that. It adds the behavioral context of 'deterministic' and 'local', which is useful, but 'with freshness' is vague and does not disclose what freshness means or how it affects results. No contradiction with 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?

A single, compact sentence that states exactly what the tool does. No filler or redundant phrasing, and the core message is front-loaded.

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

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

For a parameterless, read-only tool with an output schema present, the description is mostly complete. The one gap is the ambiguous 'with freshness' clause, which could be interpreted as return freshness metadata or a guarantee of up-to-date data. Overall the agent can invoke it correctly without further information.

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

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

The tool has zero parameters, so there are no parameter details to document. The baseline for 0 parameters is 4; the description does not add parameter information but does not need to since none exist.

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 ('Return') and names a clear resource ('Alfred's deterministic local task agenda'), which distinguishes it from sibling tools like system_status or memory_search. The qualifiers 'deterministic' and 'local' further pin down what this tool uniquely provides.

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

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

There is no guidance on when to use this tool versus its many siblings. No mention of conditions, alternatives, or exclusions. The agent is left to infer that agenda_get is for reading Alfred's task agenda, but not when that is preferable to task_complete or availability_get.

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

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

The description discloses several non-obvious behaviors beyond the readOnlyHint annotation: timed events block the day, all-day events are ambiguous context, overlapping meetings merge before gap computation, and default working hours are 09:00–17:00 local. This materially helps an agent interpret results.

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

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

The description is compact and front-loaded, with each sentence adding behavioral or parameter meaning. There is no filler or repetition of schema fields.

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 search tool with an output schema and annotations, the description covers important edge cases: all-day events, overlap merging, timezone handling, and working-hour defaults. Nothing critical is missing for correct invocation.

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

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

Schema description coverage is 0%, so the description must compensate. It clarifies timezone as an IANA name and links days to the next-few-days horizon, but it never explicitly defines min_minutes as the minimum free-gap duration, leaving one parameter under-specified.

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

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

The description states a specific verb and resource: 'Find free gaps in the synced Google Calendar.' It clearly differentiates availability lookup from siblings like agenda_get or calendar_event_propose by focusing on gap detection rather than event listing or proposal.

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

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

The description gives clear context for when to use the tool: finding open time slots in a synced calendar. It does not explicitly name alternatives or exclusion conditions, but the context is strong enough for an agent to select it appropriately among the listed siblings.

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

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

The readOnlyHint already establishes the tool is safe to call, and the description adds useful behavior: the output is deterministic, local, and generated on request rather than by schedule. This goes beyond the annotation without contradicting it. Return details are covered by the output schema.

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

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

The description is a single tight sentence with the core action front-loaded and the scheduling contrast in a short secondary clause. Every phrase contributes meaning and there is no redundant restatement of the tool name or 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?

For a low-complexity, read-only tool with no required parameters and an existing output schema, the description covers purpose and usage well. The only meaningful omission is the optional 'now' parameter, but it has a sensible default and is not required for normal invocation, so the definition is still 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 0%, so the description needed to explain the lone 'now' parameter — its format, meaning, and how null behaves. The word 'deterministic' hints that 'now' controls the evaluation time, but the description never explicitly mentions or documents the parameter, leaving a real invocation gap.

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

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

The description names a specific verb ('Render') and a distinct resource ('the deterministic local morning brief'), and clarifies the invocation mode ('on demand, not just on schedule'). This gives the tool an identity separate from sibling tools like agenda_get or journal_get.

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 clearly states when to use the tool: whenever an on-demand morning brief is needed instead of waiting for the scheduled one. It does not name explicit alternatives or when-not-to-use conditions, so it stops short of full routing guidance.

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

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

The description goes well beyond the annotations by disclosing that no external write happens until confirmation, that natural-language date phrases must be resolved to ISO 8601 timestamps, and that calendar_id accepts both friendly names and real Google ids. It also reveals the error behavior for unknown or ambiguous calendar names: return a list of writable calendars rather than guessing.

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 well structured: the opening sentence delivers the core purpose immediately, and the following paragraphs each add a distinct operational detail needed for correct invocation. There is no filler or repetitive explanation.

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

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

The description covers the safety model, the timestamp requirements, calendar_id resolution behavior, and failure behavior. It does not describe what a successful preview response contains, but for a preview tool whose main contract is 'no side effects until commit,' this is only a minor gap.

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

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

Schema coverage is only 50%, so the description compensates by adding meaning to start, end, and calendar_id. It explains timestamp formatting and resolution, and it clarifies how calendar names are handled. Only summary lacks explicit guidance, though its purpose is reasonably inferable from the context.

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

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

The description names a specific action and resource: 'Preview a calendar event write.' It also explains the two-phase nature by stating that nothing reaches Google until action_commit confirms, which clearly distinguishes this preview tool from a direct commit or create 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?

The intended use is clear: this is the preview step before action_commit, and the description gives practical instructions for resolving date phrases and passing calendar names. It does not explicitly enumerate when not to use it, but the context and sibling name action_commit make the 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?

Beyond the annotations, the description discloses that the tool returns a user-facing link and that the sign-in flow is interactive: the owner must open the URL and complete sign-in before retrying. This is important behavioral context. It does not mention side effects or connection state changes, but the annotations do not contradict the description.

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 terse sentences with no filler: purpose is front-loaded, then the required follow-up workflow, then the exclusions. Every sentence earns its place.

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

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

For a tool with one parameter and no output schema, the description covers the interactive flow and exclusions well. However, it omits valid toolkit values and doesn't explain how to verify the connection after sign-in, so an agent could still invoke it with an unsupported toolkit.

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 only parameter, 'toolkit', has no schema description (0% coverage), and the description never explicitly explains what to pass. The exclusion list implies it selects an integration, but no valid values or examples are given, so an agent may not know what to pass for an allowed app.

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

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

States a concrete verb ('Return') and resource ('Composio Connect Link') with a clear purpose: letting the owner sign in to an app. The phrase 'overflow app' is somewhat vague, and it doesn't explicitly differentiate from sibling Composio tools, so it isn't 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?

Provides a clear workflow: open the returned URL, finish sign-in, then retry the original request. It also gives a concrete exclusion list ('Not for Gmail/Calendar/GitHub/Slack/Telegram/Fitbit'). It stops short of naming alternative sibling tools or conditions for when to use composio_status or composio_execute instead.

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

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

With readOnlyHint and other annotations all false, the description carries the burden of disclosing behavior. It adds valuable detail: reads execute immediately, writes are only previewed for Telegram approval, and action_commit must not be called. It stops short of explaining the post-approval flow, but the core behavioral warning is present.

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

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

The description is three short sentences with no filler. The purpose is front-loaded, and the critical warning about action_commit is placed last without diluting the main instruction.

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

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

For a two-parameter tool with no output schema, the description covers the execution mode, the argument source, and the approval/commit warning. Missing slug semantics and read return behavior are minor gaps but leave some ambiguity for an agent that lacks broader Composio context.

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

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

Schema description coverage is 0%, so the description must compensate. It explains arguments_json as a JSON object matching input fields from composio_search, which is useful, but it does not explain slug beyond its name or how to obtain a valid slug. The compensation is incomplete.

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

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

The description states a clear verb and resource: run a Composio read now, or preview a write for Telegram approval. It also distinguishes itself from the sibling action_commit by explicitly saying never call action_commit, so the agent can tell its role apart from related 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?

It gives actionable context: arguments_json should match fields from composio_search, writes return needs_approval, and action_commit should not be called. It does not fully spell out the complete search-then-execute flow, but the usage context is clear enough to route an agent correctly.

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. The description adds that results include slugs, whether the tool writes, and required argument names, which goes beyond the annotations. It does not discuss rate limits or auth, but for a read-only search tool this is a minor gap, not a contradiction.

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

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

The description is compact and front-loaded: it states the purpose first, gives exclusions, and closes with the exact follow-up action. Every sentence earns its place with no filler.

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

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

For a simple read-only search tool, the description covers purpose, exclusions, return contents, and the next step, which is sufficient for an agent to invoke it correctly. The only material gap is the unexplained optional toolkit parameter, which prevents a perfect score.

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

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

Schema description coverage is 0%, so the description must carry the semantic load for the parameters. It does not explain what 'query' should contain beyond the general search context, and it entirely ignores the 'toolkit' parameter, which is undocumented in both the schema and the description.

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

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

The description opens with a specific action and target: 'Find overflow-app tools on Composio's free tier' with concrete examples. It also distinguishes the tool from first-party Alfred connectors and from composio_execute, the follow-up call, so an agent can tell them apart.

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

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

The description explicitly says when not to use this tool: 'Do not use this for Gmail, Calendar, GitHub, Slack, Telegram, or Fitbit' because those are first-party Alfred connectors. It also names the next step, composio_execute, and says to call it with a slug.

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

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

The description is consistent with the readOnlyHint=true annotation and adds useful context beyond it: the specific UTC month scope and what the tool reports. No destructive or mutating behavior is suggested.

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

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

One concise sentence that front-loads the resource and delivers the complete meaning. There is no filler or redundant restatement of the tool name.

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

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

For a zero-parameter, read-only status tool with no output schema, the description fully specifies what the agent can expect. Nothing needed to decide whether to call it 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?

There are no parameters, so the description carries no parameter burden. Baseline for zero-parameter tools is 4, and the description correctly specifies the tool's informational output.

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 ('Show') with a clear resource and scope: Composio connected accounts plus this UTC month's free-tier usage. This distinguishes it from sibling tools like composio_search, composio_execute, and composio_connect.

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 intended use case is clear: call this tool when reporting on Composio connected accounts or current monthly free-tier usage. It does not explicitly name alternatives or exclusions, but the zero-parameter read-only status nature makes the context sufficient.

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 the description adds behavioral context beyond that: it reads the connector_records table that syncs write to, requires no new storage or sync logic, and returns only currently-active records in reverse chronological order. This is useful and consistent with the read-only annotation.

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 first sentence is a clear, front-loaded definition of behavior. The following paragraph is somewhat long but each sentence serves a purpose: differentiating from sibling tools and clarifying that no new storage or sync logic is needed. It is appropriately detailed without filler.

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

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

For a read-only tool, the description covers what it returns, ordering, data source, and how it differs from digest tools. However, because schema-level parameter documentation is entirely absent and the description does not define record_type or limit semantics, an agent may still be uncertain how to correctly invoke the tool for a specific record type.

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

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

The input schema has no descriptions (0% coverage), and the description does not explain the limit or record_type parameters, their defaults, or accepted values. It only clarifies the connector scope and gives one example involving gmail-sync unread-message records, leaving the agent to guess how filtering and limiting actually behave.

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

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

The description opens with a specific action and resource: 'Return one connector's currently-active synced records, most recently observed first.' It also explicitly contrasts this tool with brief_get and agenda_get, positioning it as the only direct accessor of raw connector content, so it is clearly distinguishable from siblings.

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

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

The description gives clear context by stating that brief_get/agenda_get provide a folded digest, while this tool exposes raw synced records directly. It doesn't explicitly say 'use this when you need raw records and use brief_get/agenda_get when you need a digest,' but the contrast is strong enough to guide selection.

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

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

Annotations already declare readOnlyHint=true, covering the tool's non-mutating nature. The description adds a useful behavioral guarantee beyond annotations: the report excludes credentials and synced content, which is important contextual information for an agent. No contradiction with 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 description is a single sentence that front-loads the operation and resource, then immediately constrains the scope with a clear exclusion. Every word contributes meaning; there is no filler or repetition.

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

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

For a parameterless, read-only status tool with an output schema, the description is complete. It states what is reported, what is deliberately excluded, and the annotations cover mutability. No critical information needed to invoke the tool 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?

The input schema has zero parameters and schema coverage is 100%, so there is no missing parameter documentation to compensate for. The description reinforces the no-argument aggregate nature by saying 'each connector's health' rather than implying a single-connector filter.

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 ('Report each connector's health') and clarifies what the report will never contain ('credentials or synced content'). It clearly states the tool's purpose, though it does not explicitly name sibling tools like composio_status or connector_records_get to sharpen differentiation.

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

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

The phrase 'never its credentials or synced content' provides an explicit when-not boundary, steering agents away from using this tool for credential or content retrieval. However, it does not name alternative tools or state when to prefer this tool over system_status or composio_status.

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

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

The description discloses that despite the name 'forget', this tool is not destructive by itself and that deletion is deferred until action_commit confirms. It adds meaningful policy context about strong-confirm and unattended MCP clients, which is especially valuable given destructiveHint=false could otherwise be confusing.

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 first sentence is clear and front-loaded with the core behavior, and the second provides important policy context. The phrasing is a bit verbose and relies on unexplained 'Decision 8' jargon, but every sentence contributes meaningful 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?

The description explains the critical two-phase behavior and client safety constraint, but it omits details about what the preview response looks like, what happens to pending deletions before commit, and how the reason parameter is used. Since there is no output schema, additional behavioral detail would improve completeness.

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

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

Schema description coverage is 0%, and the description does not explain the meaning or usage of memory_id or reason. The tool's purpose implies memory_id identifies the memory, but reason is left entirely unexplained, so the description does not compensate for the missing parameter documentation.

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

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

The description states a specific verb ('Preview deleting') and resource ('one memory'), and immediately clarifies the key limitation that nothing is deleted until action_commit confirms it. This distinguishes the tool from action_commit and makes its role in the deletion workflow clear.

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 explains the two-phase workflow and explicitly warns that an MCP client cannot delete in a single call because deleting data is classified as strong-confirm. It does not enumerate alternatives, but it names action_commit as the confirming step, giving enough context for when to use this tool.

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

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

Despite readOnlyHint=false, the description discloses that no external write reaches GitHup until a later commit — genuinely load-bearing context beyond what the annotations provide. This also aligns with destructiveHint=false and clarifies the non-idempotent preview trait. It doesn't cover auth requirements or failure modes, but the core safety trait is disclosed.

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

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

Two short sentences with zero waste, front-loading the primary purpose ('Preview a GitHup issue creation') and then the critical behavioral caveat. Every word earns its place.

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

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

For a 3-parameter tool with no output schema, the description covers purpose, the preview/commit boundary, and names the committing sibling. A minor gap is that it doesn't hint what the preview returns (e.g., a proposal to hand to action_commit), but the simple parameter set and annotations keep this adequate.

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

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

Schema description coverage is 0%, so the description carries the burden. It contextualizes repository/title/body as the components of a GitHup issue and implies they will later be committed, but it adds no per-parameter format or constraint details (e.g., 'owner/repo' syntax). The parameter names are self-evident, making the gap moderate rather than severe.

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 ('Preview') and resource ('GitHup issue creation'), and the second clause ('nothing reaches GitHup until action_commit confirms it') sharply differentates it from the complementary sibling action_commit. An agent can immediately tell this is the staging step, not the publishing step.

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 explicitly places the tool in a two-phase workflow: preview here, confirm with action_commit. It names the sibling that completes the operation, which gives clear context for when to pair them. It does not enumerate when-not-to-use conditions, but the propose/commit boundary is explicit enough.

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

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

Annotations are all false, so they do not convey safety or side effects. The description's 'Append' indicates a write operation, consistent with readOnlyHint=false, and it adds the 'free-text' qualifier, but it does not disclose persistence, error behavior, or any side effects beyond the obvious mutation. It neither adds rich context nor contradicts 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?

A single, front-loaded sentence with zero waste. Every word contributes to clarity, and the action ('Append') is stated first. It is appropriately sized for the tool's simplicity.

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

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

For a one-parameter append tool with no output schema, the description provides enough to call it correctly: it identifies the resource, the action, and the nature of the parameter. It omits any mention of return values or side effects, but given the tool's simplicity and absence of an output schema, this is a minor gap.

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

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

Schema description coverage is 0%, so the description must compensate. 'Free-text' clarifies that the 'text' parameter is the raw content of the journal entry with no formatting constraints, adding meaning beyond the bare string type. It does not specify limits or optionality beyond the required flag, but for a single free-text parameter this is adequate.

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 ('Append') and resource ('gratitude journal entry'), clearly distinguishing it from siblings like mood_record (structured mood tracking) and journal_get (retrieval). The purpose is unambiguous and immediately actionable.

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

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

No guidance is provided on when to use this tool versus alternatives such as mood_record or journal_get. The simple action is implied, but the description does not explicitly state context or exclusions, leaving the agent to infer usage from the name and siblings alone.

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

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

The description adds valuable behavioral detail beyond the annotations: it states that the date is stored as an ordinary task with a next-occurrence due_at plus an annual reminder job, and that dates surface in the morning brief under 'Birthdays & dates.' It also explains timezone behavior relative to daylight saving. This goes well beyond the minimal readOnly/destructive hints, though it does not disclose duplicate handling or update semantics.

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

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

The description is three sentences with no filler: purpose, storage/surfacing behavior, and the two parameter clarifications that matter most. It is front-loaded with the primary use case and keeps supporting details compact. Every sentence earns its place.

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

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

Given seven parameters, minimal annotations, and no output schema, the description covers the main operational context: recurrence model, where dates appear, timezone semantics, and year handling. It does not explicitly state what the response will be or how chat_id is used, but the overall behavior is clear enough for an agent to invoke it confidently in most cases.

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

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

Schema description coverage is 0%, so the description must compensate. It does explain the two least obvious parameters: timezone is an IANA name and year is optional and only used for 'turns N.' However, label, month, day, chat_id, and kind are left to their names or schema defaults; in particular, kind values beyond 'birthday' are not specified even though 'other annual date' is mentioned.

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

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

The description opens with a specific verb and resource: 'Remember a birthday or other annual date and remind on that day each year.' It clearly differentiates from calendar_event_propose by stating 'not a separate calendar' and from important_dates_get by the set-vs-get relationship. The purpose is unambiguous and immediately useful for tool selection.

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

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

The description gives a clear condition for use: recurring annual dates that should remind yearly. It implicitly excludes calendar events and one-off reminders by describing the storage as an ordinary task plus annual reminder job, and by mentioning the morning brief/weekly window. It does not explicitly name alternatives like reminder_set or calendar_event_propose, so the guidance is strong but not fully explicit.

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

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

Annotations already mark the tool as read-only, and the description adds practical behavioral detail: the default seven-day window, the effect of passing a larger window, and the meaning of passing 0. This goes beyond the annotation and helps the agent reason about results.

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

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

The description is compact, front-loaded with the core purpose, and every subsequent sentence adds useful behavioral or parameter guidance. No wasted words or redundant restatement of the tool name.

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

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

For a simple, single-parameter read-only listing tool with an output schema, the description covers the essential semantics: what is listed, the default horizon, and how to override it. Nothing important is missing for an agent to select and invoke it correctly.

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

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

Schema description coverage is 0%, but the description fully compensates by explaining the only parameter, within_days: its default, how to extend the window, and what 0 means. The parameter name clarifies the unit, so an agent can invoke it correctly.

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

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

The description opens with a specific verb and resource: 'List upcoming birthdays and important dates'. It also scopes the behavior to 'inside the weekly window', which distinguishes it from sibling tools like important_date_set and agenda_get without ambiguity.

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

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

The description provides clear usage context: it aligns with 'what's coming up this week' questions and the morning brief, and explains how to adjust the time horizon. It does not explicitly name alternative tools or say when not to use it, but the context is strong enough for an agent to know when this tool fits.

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 the readOnlyHint annotation, the description reveals a non-obvious rule: trend direction is only named with at least five days of check-ins and a 0.5 difference, and otherwise mood_trend.reason explains the null. This prevents an agent from misreading a null trend as 'no change,' which is exactly the kind of hidden behavior that matters.

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 first sentence is a clear front-loaded statement of function, and the second adds a necessary qualification about trend naming. Both sentences earn their place, and the prose is compact for the behavioral nuance it conveys.

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 names the major return components (mood check-ins, gratitude entries, mood trend) and explains mood_trend's null behavior, so an agent understands what it will receive. It does not describe entry-level fields or ordering, but those are less critical for correct invocation given the simple optional parameter.

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 only parameter, days, has no schema description and the description does not explicitly explain it, though 'recent' hints at the lookback window. The schema's type, name, and default make the parameter fairly self-evident, so the lack of additional detail is not severely penalized.

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

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

The description opens with a specific verb and resource: 'Return recent mood check-ins, gratitude entries, and mood trend.' This clearly identifies what the tool retrieves and distinguishes it from the record-creation siblings like mood_record and gratitude_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 implies the tool is for retrieving recent journal/mood data, but it does not explicitly state when to use it over alternatives such as mood_record or gratitude_record. Usage must be inferred from the tool's name and domain rather than from direct 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 are all false, so the description carries the burden of explaining behavioral impact. It usefully discloses that the operation preserves superseded history and evidence, indicating a non-destructive correction. It does not mention return values or failure behavior, which keeps it from a 5.

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

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

A single sentence with no filler: the action is front-loaded and the preservation guarantee is stated compactly. It is appropriately concise for a simple two-parameter 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?

For a two-parameter mutation with no output schema, the description covers the core operation and its principal side effect. It is slightly thin on return or error semantics, but not critically incomplete for selecting and invoking the tool correctly.

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

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

Schema description coverage is 0%, but the parameter names are fairly self-explanatory and the description reinforces the replacement intent. It does not explicitly define memory_id or replacement_statement, nor does it mention constraints such as whether the memory must already exist.

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 ('Correct one recalled memory') and adds a distinguishing detail: preserving superseded history and evidence. This clearly separates it from sibling tools like memory_add, memory_delete, and even a plain memory_update.

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 correction intent is clear, but the description does not explicitly state when to prefer this over memory_update or when not to use it. Usage is implied by the word 'Correct' rather than stated as a condition or with named alternatives.

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

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

Annotations offer no safety signals, so the description carries the full burden. It does communicate that this records feedback and implies a write operation, but it does not disclose whether repeated feedback overwrites previous feedback, whether it is associated with a specific query, or what effect it has on future recall. For a mutating tool with no annotation support, this is a notable gap.

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

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

The description is a single, focused sentence with no fluff. It front-loads the action and immediately defines the categories of feedback.

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

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

For a simple three-parameter tool with no output schema, the description covers the core purpose and the expected feedback categories. It is adequate but incomplete: it does not explain the relationship between 'query' and 'memory_id', nor does it state when feedback should be recorded or what downstream behavior it influences.

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

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

Schema description coverage is 0% and there are no enums. The description helps by naming the possible outcome values ('relevant, irrelevant, or incorrect'), which clarifies the 'outcome' parameter. However, it gives no explicit meaning or format for 'query' and 'memory_id', leaving those to be inferred from their names.

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

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

The description uses a specific verb, 'Record', and a clear resource: whether a recalled memory was relevant, irrelevant, or incorrect. This is concrete and actionable, though it does not explicitly differentiate itself from sibling tools like memory_correct beyond the word 'feedback.'

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 of use is implied: it is for recording feedback about a recalled memory. However, it does not explicitly state when to use this over memory_correct, forget, or other memory-related sibling tools, nor does it mention prerequisites like having a memory_id from a prior search.

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 indicate safe read-only behavior (readOnlyHint=true), so the description need not repeat that. It adds some behavioral context by limiting the search to 'local memory anchors' and 'one-hop active graph context', but it does not disclose result pagination, matching semantics, or other runtime behavior. This is adequate but not rich.

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

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

A single, front-loaded sentence with no filler. Every word carres meaning: 'Search' gives the operation, 'local' scopes it, and 'one-hop active graph context' defines the extent of results.

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 search tool with one required parameter, the description is mostly complete for invocation. However, with no output schema present, it does not fully describe the return format or how 'active graph context' is represented, leaving some ambiguity for an agent interpreting 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?

The input schema only shows a required string 'query' with no meaningful description. The tool description minimally compensates by clarifying that the query searches local memory anchors and their one-hop graph context. It does not specify query syntax, matching behavior, or format expectations, so the meaning is only partially covered.

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 ('Search'), a clear resource ('local memory anchors'), and a scope qualifier ('one-hop active graph context'). It is immediately distinguishable from the sibling memory tools like remember, memory_correct, memory_feedback, and forget, which are write/destructive operations.

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 verb 'Search' implicitly conveys this is the tool for retrieving memory content rather than mutating it, but the description does not state when to prefer it over a sibling or mention any exclusions/alternatives. Usage is implied by the operation name, not explicitly guided.

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

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

The description discloses a key behavioral guarantee beyond the annotations: no external side effect until a human confirms. This is valuable safety-relevant context. It does not contradict readOnlyHint=false because the tool may still perform local work or prepare a draft, but the key external behavior is clarified.

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 communicats purpose and the most important behavior with zero waste. Every word earns its place.

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

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

The description is adequate for a simple preview tool and clearly states the safety guarantee. However, it does not describe the return value or what the agent should expect after invoking it, and param-level guidance is absent. With no output schema, this leaves a modest gap.

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

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

Schema description coverage is 0%, and the description adds no additional meaning for to, subject, or body. The parameter names are self-explanatory, but no format, constraints, or examples are provided, leaving the description to carry the burden it does not shoulder.

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 ('Preview') with a clear resource ('Gmail draft') and adds a decisive scope qualifier: nothing reaches Gmail until human confirmation. This distinguishes it from send-oriented sibling tools like message_send_propose, even without naming an alternative.

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

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

It implies usage: use this to preview before anything is sent or reaches Gmail. However, it does not explicitly state when to prefer this over alternatives, nor mention any exclusions or preconditions.

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 the boolean annotations (all false), the description discloses a real behavioral trait: Telegram attaches approve/cancel buttons to this proposal. It also adds the operational instruction not to paste the letter into chat, which is useful context an agent would not get from the schema or annotations. It does not go into what happens after an approve, but the word 'preview' plus approve/cancel sufficiently conveys the interaction model.

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, purposeful sentences. The purpose is front-loaded in the first sentence, and the second sentence supplies the critical Telegram behavior and a safety instruction. There is no filler or repetition.

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

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

For a simple 3-string-parameter proposition tool, the description explains the workflow (preview, approve/cancel, avoid pasting body content) well enough for an agent to invoke it sensibly. It lacks parameter detail and does not specify the post-approval effect, but the approve/cancel model and the tool's propose semantics cover the main decision point.

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

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

Schema description coverage is 0%, so the description should compensate for the undocumented to/subject/body parameters. It only indirectly refers to 'the letter' and 'Gmail', providing weak semantic context, but it never clarifies the meaning or format of individual parameters. An agent still has to infer that 'to' is a recipient email address and 'subject' is an email subject.

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

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

The description opens with a specific action and resource: 'Preview sending Gmail.' It clearly identifies the tool as the approval-gated send proposition for email, and the mention of Telegram approve/cancel distinguishes it from a plain drafting tool like message_draft. The purpose is unambiguous from the first sentence.

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

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

The description gives clear context for use: this is the preview/send-proposal path for Gmail, and it explicitly warns the agent not to paste the email body into chat. It does not enumerate exclusions or name alternatives like message_draft, so it falls just short of fully explicit when-not-to-use guidance.

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

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

Annotations indicate a non-read-only, non-destructive operation but give little else. The description adds that mood is stored separately from habits, which is useful context, but it does not specify whether each call appends a new entry or overwrites, nor does it mention any side effects or permissions. Given minimal annotation coverage, this is a moderate gap.

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

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

Two concise sentences with no waste: the first front-loads the core action and optional note, the second adds the distinction from habits and the pointer to journal_get. Every sentence earns its place.

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

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

For a simple tool with only two parameters and no output schema, the description gives enough to call it correctly: the rating range, optional note, and the workflow for reviewing entries. It is complete for the tool's complexity.

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

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

The description directly states the rating is on a 1–5 scale and that the note is 'optional short', which adds meaning beyond the bare schema (which has no descriptions). This compensates well for the 0% schema description coverage.

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

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

The description states a clear action ('Record') on a specific resource ('mood check-in') with a defined scale (1–5). It explicitly contrasts with habit tracking and points to journal_get for review, distinguishing it from sibling tools like gratitude_record and journal_get.

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

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

The description provides a direct pointer to journal_get for reviewing entries and naming trends, implying this tool is for capturing data rather than analysis. While it doesn't list explicit exclusions, the context is sufficient for an agent to decide when to use this tool vs. alternatives.

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

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

Annotations provide minimal safety info (readOnly=false, not idempotent, not destructive). Description adds meaningful behavior beyond annotations: each firing re-reads task state, completing the task anywhere silences future nags, and final attempt is explicitly labeled. This gives the agent essential operational expectations.

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 with key behavior front-loaded. Every sentence contributes: mechanism (repeat), termination conditions, re-read behavior, and final-attempt labeling. Could be more compact but no filler.

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

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

For a 6-parameter tool with 0% schema coverage and no output schema, the description is inadequate. It explains the overall mechanism but omits parameter formatting/semantics entirely—most critically what text expects, how task_id links to a task, how first_run_at should be formatted, and the meaning of interval_hours. The return behavior is also unstated.

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

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

Schema description coverage is 0%, so the description carries the full burden of parameter explanation, and it fails to do so. It never explains text, chat_id, task_id, first_run_at, max_attempts, or interval_hours. The behavioral description implies some parameter meanings (task, attempts, reminders) but doesn't map parameters to their roles.

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?

Description states a specific verb+resource: repeats a reminder until task completion or attempts run out. Distinguishes itself from the sibling reminder_set by describing the conditional repetition behavior, though it doesn't name the sibling 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?

Description implies usage context clearly: use for reminders that should persist until the linked task completes. States the stopping conditions (task completion or attempts exhausted). Doesn't explicitly state when not to use it or name alternatives, but behavioral distinction is implicit.

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, and the description does not contradict them. It adds useful content context ('local owner node', 'evidence-backed relationships') but does not provide deeper behavioral disclosures beyond what the annotations imply.

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, tightly worded sentence with the verb front-loaded. Every word earns its place, and there is no redundant or promotional filler.

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

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

For a zero-parameter, read-only tool with no output schema, the description is sufficiently complete. It names both components of the return value (local owner node and profile relationships) and the complexity is low enough that little else is needed.

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

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

The tool has zero parameters and full schema coverage, so the baseline of 4 applies. There are no parameter semantics for the description to add.

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 ('Return') and a specific resource ('local owner node and current, evidence-backed profile relationships'). This clearly distinguishes the tool from its siblings and leaves no ambiguity about what it does.

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

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

Usage context is implied by the tool name and the description, but there is no explicit statement about when to use profile_get versus alternative tools. It does not mention exclusions or provide routing guidance among the many sibling 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 mark this as read-only, lowering the burden on the description. The description adds useful behavior: it fetches live data via GitHub search and applies staleness logic based on updated_at and stale_after_days. The phrase 'marks PRs stale' is slightly ambiguous, but in a read-only list context it clearly means computed labeling rather than a mutation, so there is no contradiction.

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

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

The description is two dense sentences with no filler. The main purpose is front-loaded, and the second sentence adds only high-value behavioral details about the live snapshot and staleness calculation. Every word earns its place.

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

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

This is a simple read-only tool with one optional parameter and an output schema. The description covers the resource, the selection criteria, the data source, and the one configurable behavior. There is nothing an agent needs to know in order to invoke it correctly that 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?

The schema has 0% description coverage, so the description must explain the only parameter, stale_after_days. It does so by defining staleness as updated_at being older than that number of days, which gives the agent a clear semantic meaning. It does not state bounds or exclusivity, but the default is in the schema and the integer meaning is clear.

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 open GitHub pull requests you authored or were asked to review.' It clearly scopes the tool's behavior and distinguishes it from notification-based data by noting it fetches a live snapshot via GitHub search. No sibling tool appears to serve the same purpose, so the intent is unambiguous.

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

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

The description tells the agent when to use the tool: whenever open PRs authored by or assigned to the user need to be listed. It also provides important context by clarifying this is a live search snapshot, not a notifications sync. It does not name an alternative tool, but none of the siblings directly compete, so the guidance is sufficient.

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 show this is a non-readonly, non-idempotent mutation, and the description adds the useful side effect that the calling client is recorded as actor. It does not disclose potential duplicate handling, overwrite behavior, scoping effects, or consequences beyond that. The added detail is meaningful but thin.

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 states the core action and an important side effect with no filler. It is as concise as a useful description can be.

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 definition is too thin for correct invocation: it omits parameter semantics, has no output schema, and gives no route to sibling memory operations. Even though the tool is conceptually simple, an agent needs more context about kind/sensitivity and when to store versus correct or forget.

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

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

Schema description coverage is 0%, so the description has the full burden of explaining statement, kind, and sensitivity, but mentions none of them. An agent cannot infer what values to supply for kind and sensitivity from this text.

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

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

The description names a specific action ('Store') and resource ('confirmed local memory'), clearly distinguishing it from retrieval tools like memory_search and deletion tools like forget. The phrase 'calling client is recorded as actor' further pins down what this tool does. It loses the fifth point because it does not explicitly name sibling alternatives or define what 'confirmed' means.

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?

Aside from implying that the memory should be 'confirmed' and 'local', there is no guidance on when to choose this tool over memory_correct, memory_feedback, or forget. No explicit when-to-use, when-not-to-use, or alternative routing is provided.

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

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

The description discloses important behavior beyond the annotations: reminders are delivered only via Telegram, chat_id must already be paired, and daily reminders follow wall-clock time with an IANA timezone for DST safety. Annotations are all false, so the description carries this burden and does it reasonably well, though it does not mention cancellation, deduplication, or persistence behavior.

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

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

The description is moderately sized and front-loaded with the primary action and core prerequisite. Each paragraph addresses a distinct concern (delivery context, chat_id fallback, daily/timezone semantics) without significant 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?

The description covers the main Telegram-specific complexities and the daily/timezone interaction, which are the non-obvious parts. However, with no output schema and no description of run_at format or task_id, an agent still has meaningful gaps to resolve before calling 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?

With 0% schema description coverage, the description adds meaning for chat_id, daily, and timezone, but leaves the required run_at format and the purpose of task_id unexplained. This is partial compensation rather than full coverage of the parameter space.

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

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

The description opens with a specific verb and resource, 'Schedule a Telegram reminder', and adds a key prerequisite about a locally paired chat_id. It is clear but does not explicitly differentiate from sibling scheduling tools like task_schedule or nag_until_done.

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

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

It provides clear context for when chat_id is required versus when it can be read from ALFRED_TELEGRAM_CHAT_ID during an inbound Telegram turn, and explains the daily/timezone constraint. It stops short of naming alternatives or stating when not to use this tool.

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

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

The readOnlyHint annotation already declares this as a read-only operation, and the description adds meaningful context by specifying 'non-sensitive', 'local', and 'schema status'. This helps an agent understand the data scope without contradicting 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 description is a single, tightly scoped sentence with no filler. Every qualifier ('non-sensitive', 'local', 'health and schema status') contributes directly to tool understanding.

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

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

For a zero-parameter status tool with readOnlyHint and an output schema, the description is complete. It identifies what is returned and the scope, and the output schema can define the actual return structure without burdening the description.

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 schema description coverage of 100% is vacuous. With no parameters to document, the baseline of 4 applies and the description does not need to add parameter semantics.

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

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

The description uses a specific verb ('Return') and clearly identifies the resource: Alfred's non-sensitive local health and schema status. The qualifiers 'local' and 'non-sensitive' distinguish it from sibling status tools like composio_status and connector_status.

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

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

There is no guidance on when to use this tool versus alternatives. While the 'local' qualifier implies it is for Alfred's own status rather than external connectors, no explicit comparison or exclusion is provided for sibling status 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 idempotentHint=true, and the description repeats that behavior with 'completing an already-completed task is a no-op.' It does not add much beyond the annotation, though it does clarify the 'open task' precondition. No contradiction with 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 description is a single, front-loaded sentence with zero filler. It states the core action and the only edge case in compact form.

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 one-parameter tool with annotations covering idempotency, the description is nearly sufficient. It lacks explicit return behavior or failure details, but those are less critical given the tool's simplicity.

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

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

The schema has a single task_id property with 0% description coverage. The tool description does not explain what task_id refers to, how to obtain it, or any format expectations, so the description does not compensate for the schema's lack of parameter guidance.

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: 'Mark an open task completed.' It clearly identifies the action and scope, and the no-op qualifier distinguishes this from task creation/scheduling tools like task_upsert or task_schedule.

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

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

The description gives clear context: use this when an open task should be marked completed. It does not explicitly name alternatives or when-not-to-use conditions, but the context is straightforward enough for selection among siblings.

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

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

Annotations only say it's not read-only and not destructive. The description goes far beyond: it explains that the instruction is queued as an ordinary agent turn ('the reply arrives looking exactly like any other answer'), warns that a job elsewhere silently never fires, and details the chat_id fallback behavior from ALFRED_TELEGRAM_CHAT_ID. It also clarifies daily/timezone handling. This is rich behavioral context not present in the schema or 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?

Though longer than typical, every sentence earns its place. The core action is stated first, then the critical distinction from reminders, then behavior, then parameter notes. No fluff or redundancy; the structure front-loads the most 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?

The description is complete for a scheduling tool: it covers what it does, when to use it, how the execution works, parameter formats, special cases (Telegram chat_id fallback), and a critical operational warning. No output schema exists, but that is not needed for a fire-and-forget scheduling action. 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?

Schema description coverage is 0%, so the description must explain parameters. It does well for the non-obvious ones: run_at must be ISO-8601 with offset, daily repeats it and then timezone must be IANA, chat_id may be omitted under a specific condition. It does not explicitly state that prompt is the instruction to run, but that is inferable from the tool's purpose and description. It adds significant meaning beyond the bare schema.

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

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

The description opens with a clear verb–resource pair: 'Run an instruction later and send the answer to a paired chat.' It immediately distinguishes itself from the sibling reminder_set by explaining when to use scheduling over a reminder ('when the user wants something *done* at a time rather than something *said*'), and gives a concrete example. This makes it impossible for an agent to confuse it with other tools.

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

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

The description provides explicit when-to-use guidance ('Use this, not a reminder...'), a concrete example, and a strong when-not-to-use instruction ('Never schedule this kind of work in your own runtime's cron'). It also explains the alternative (a reminder) and why it would be inappropriate, leaving no ambiguity about selection.

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

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

The second sentence adds behavioral context beyond annotations by stating the operation is automatic, reversible, and requires no approval. It also clarifies that updates only affect title and due date, which is useful for the agent. This does not contradict the readOnlyHint, destructiveHint, or idempotentHint 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 description is brief and front-loads the core behavior in the first sentence. However, the 'Decision 8' reference is cryptic and unexplained, making the second sentence less useful than it could be.

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

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

The description covers the essential create/update logic and the role of task_id, which is enough for basic invocation. Yet it omits return-value expectations, error behavior, and any guidance on how task_id should be obtained; the unexplained 'Decision 8' reference also leaves a 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?

With 0% schema description coverage, the description compensates partly by explaining that task_id selects update mode and that title and due date are the fields manipulated. It does not explain due_at's ISO format or the meaning of null/omitted due_at, leaving the agent to rely on the schema for those details.

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

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

The description clearly states the tool creates a task or updates an existing task's title/due date when task_id is provided. It names the specific resource and action, though it does not explicitly distinguish itself from sibling tools like task_complete or task_schedule.

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 internal routing guidance: create when task_id is absent, update when task_id is present. However, it does not explain when to choose this tool over alternatives or when not to use it, leaving sibling selection implicit.

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 declare readOnlyHint=true, and the description is consistent. The description adds valuable behavioral detail beyond the annotation: it groups by thread_id, drops messages carrying List-Unsubscribe headers, and warns that older rows may lack thread_id/list_unsubscribe unless a backfill is run. This gives the agent a realistic picture of data completeness and filtering 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?

Three sentences with no filler: the main action is front-loaded, the second sentence explains the core filtering logic, and the third is a compact operational note about the backfill command. Every sentence earns its place.

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

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

Given there are no parameters and an output schema exists, the description fully covers what an agent needs to decide whether to call the tool and what to expect: source, unread/active filter, newsletter exclusion, and a data-quality caveat. Nothing critical 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?

The input schema has no parameters, so there are no call arguments to document and schema coverage is effectively 100%. The description mentions internal fields like thread_id and list_unsubscribe, but those are implementation details rather than invocation parameters, so the baseline score for zero parameters 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 ('List'), a clear resource ('unread Gmail threads'), and the intended outcome ('that look like they need a reply'). The second sentence sharpens this by explaining that it groups by thread_id and drops List-Unsubscribe-bearing newsletters, making the tool's niche unambiguous.

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

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

Provides clear operational context: the tool is for triaging active unread threads that plausibly need a reply, and explicitly excludes newsletter-style List-Unsubscribe messages. It also gives a concrete data prerequisite with the backfill command. It does not name alternatives or state explicit when-not-to-use cases, but no sibling tool appears to cover this same niche.

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