TeamMeet

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

With no annotations, the description carries the full burden, and it does disclose one important behavioral trait: the generated image is published into the meeting and visible to all participants, making this a broadcast/mutation rather than a private fetch. It says nothing about cost, latency, rate limits, failure modes, or whether the image is also returned to the caller.

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

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

One sentence, front-loaded with the action and ending with the side effect; every clause earns its place and there is no filler.

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

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

For a 3-parameter tool with no annotations and no output schema, the description is thin: it omits the existence and purpose of the 'kind' selector, gives no meeting-identifier format, and does not say what the caller receives back. It is enough to attempt a call but not enough to call it correctly on the first try.

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

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

Schema coverage is only 33% (prompt and meeting have no schema descriptions), so the description must compensate. It loosely maps both required params — 'from a description' → prompt and 'in the meeting' → meeting — but gives no format guidance for the meeting identifier (ID vs. name) and never mentions the 'kind' parameter or when to choose a diagram/infographic/meme over plain imagery.

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 ('Generate a picture') and a specific effect ('put it in the meeting for everyone to see'), so an agent knows both the creation and delivery behavior. No sibling tool does anything similar (all siblings are notes/tasks/transcript/meeting-control), so differentiation is implicitly satisfied rather than explicitly argued.

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

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

There is no statement of when to use this versus alternatives, no prerequisites (e.g. must the bot already be in the meeting?), and no exclusions. The only hint of context is the phrase 'in the meeting for everyone to see', which implies a live-meeting scope but is never framed as guidance.

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

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

With no annotations, the description bears the full disclosure burden, and it does add real behavioral value: every item carries a verbatim quote and unverified items are flagged rather than asserted as fact. However, it omits read-only/mutation status, what happens when the meeting is unknown or not yet processed, and any sense of result size or paging.

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

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

Two sentences, no filler, and the substantive promise (quote-backed, verified-vs-unverified items) is front-loaded. Every clause carries information an agent cannot get from the name alone.

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

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

With no output schema and no annotations, the description usefully characterizes the return content, which covers part of the gap. It is still incomplete for invocation: the sole input parameter is undefined and there is no guidance on failure modes or result shape.

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

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

The single required parameter 'meeting' has 0% schema description coverage, and the description never mentions it — not whether it is an ID, a title, or a room handle. The one place the description could compensate for the schema gap is exactly where it is silent.

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 concretely what the tool returns: decisions, open questions, actions and live disagreements extracted from a room's conversation, with verbatim-quote verification. That distinguishes it from siblings like get_transcript (raw transcript) and get_task (task records). It stops short of a clean verb+resource framing ('List notes for a meeting'), so it is clear but slightly atmospheric.

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

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

There is no statement of when to reach for this tool versus get_transcript, get_task, my_tasks, or list_meetings. The agent must infer the selection rule purely from the return content described, with no explicit alternatives or exclusions.

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

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

With no annotations, the description carries the full burden, and it does a solid job disclosing the returned payload in concrete terms (speaker identity, prior transcript lines with microphone source, linked fix request). Read-only behavior is strongly implied by 'get' and 'in full', though side effects, permissions, and error behavior are not explicitly addressed.

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 that front-loads the core claim ('One task ... in full') and then enumerates contents. It is compact and waste-free, though the colloquial phrasing ('the words the person asked in', 'the microphone it came in on') is slightly less crisp 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?

With no output schema, the description must explain return values, and it does so thoroughly for a read tool. What is missing is minor: no error/not-found behavior and no explicit confirmation that the call is side-effect free, which a strictly complete definition would state.

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

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

There is a single required parameter with 100% schema description coverage ('The task id, tmt_…'), so the schema already does the work. The description adds no format, sourcing, or edge-case detail beyond implying the task comes from a call. Baseline 3 is appropriate.

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

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

The description makes clear this returns a single task in full, enumerating the payload: the requestor's words, their identity, preceding call lines with microphone attribution, and any linked fix request. The verb is implicit ('one task ... in full') rather than stated, and it never contrasts with siblings such as my_tasks or update_task, so it falls short of a 5.

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

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

Usage is only implied: 'one task handed to you from a call' hints that this is the follow-up lookup after a task is surfaced, presumably via my_tasks. There is no explicit statement of when to prefer this over listing tasks or when not to call it, and no mention of what happens with an invalid task id.

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

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

With no annotations, the description is crucial for transparency. It discloses the critical behavioral trait that speaker attribution is high-fidelity ('not a guess from a mixed audio stream'), managing the agent's expectations regarding data accuracy.

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, using two highly effective sentences. The primary value proposition (high-quality attribution) is front-loaded and immediately evident.

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

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

Given the small parameter set (2) and the complete schema coverage, the description adds exactly the right amount of high-value behavioral context regarding data reliability, making it fully 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?

Since the schema coverage is 100%, the parameter definitions already cover the schema requirements. The description does not add significant semantic value beyond the basic definitions of the meeting code or the since timestamp.

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 tool purpose is stated explicitly: retrieving 'The full transcript of a meeting, with who said each line.' This clearly distinguishes it from sibling tools like get_notes or get_task.

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?

While it doesn't explicitly state 'when' to use it versus other tools, the description strongly implies its use case is for high-fidelity transcripts due to its detailed explanation of speaker attribution quality.

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

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

With no annotations, the description carries the full burden. It does disclose the downstream effect well — the recipient sees the task in the call and forwards it to their Claude with one press — which is real behavioral context. It says nothing about what happens if the name doesn't match a participant, whether the handoff is confirmable or reversible, or what the caller observes on success or failure.

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

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

Two sentences with zero waste: the action and its effect are front-loaded, followed immediately by the one non-obvious naming constraint. A minor marketing tone ("with one press") but it conveys useful mechanics rather than filler.

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

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

For a three-required-parameter action with no annotations and no output schema, the description explains the mechanism and the naming requirement but omits failure behavior, what happens if no such participant exists, and what the caller gets back. Adequate to attempt a call, not 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 coverage is 67%; `to` and `task` are documented in the schema, and the description largely repeats them. The undocumented `meeting` parameter is only obliquely covered by "from the call you are in," which hints it is the current call but does not confirm the identifier format. Net effect is roughly baseline.

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

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

The description gives a specific verb and resource: it hands a task off to another participant's agent from within the current call. That is clearly distinct from speak, send_message, or send_notetaker, though the description never names a sibling to sharpen the contrast.

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?

"From the call you are in" implies the operating context (an active call with other participants) and "Name the person as they appear in the call" gives a usage constraint. However, there is no explicit guidance on when to use this instead of send_message or a task tool, and no stated preconditions or exclusions.

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

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

With no annotations, the description carries the full behavioral burden. It usefully discloses that speaker labels are preserved, chats are filed as chats, and the tool returns a meeting id and link, but it omits important import behavior such as duplicate handling, size limits, permissions, and error behavior.

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

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

The description is front-loaded with the core action and then lists supported formats efficiently. The long format enumeration is justified because it directly helps an agent decide whether a given input is supported, though it could be slightly tighter.

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

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

For a multi-format import tool with no output schema, the description does well by naming supported formats, explaining preservation behavior, and stating the return value. It is still missing operational details around duplicates, permissions, and failures, but the core invocation context is present.

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

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

Schema description coverage is 100%, so parameter meanings are already well documented in the input schema. The description adds context about filename extensions indicating format and date, but this largely overlaps with the schema rather than adding substantial new 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 and resource: importing an external meeting transcript or chat log into the dashboard. It clearly distinguishes this from retrieval-oriented siblings such as get_transcript by emphasizing import from another tool and enumerating supported source formats.

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

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

The description makes the use case clear: import when you have a transcript or chat file from another tool. It lists many supported formats and sources, but does not explicitly state when not to use it or name an alternative sibling 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?

With no annotations, the description carries the full burden and does well: it discloses that you appear under a derived display name, that your presence is announced in the call chat, that any participant can remove you, and that joining is gated on the owner being signed in or the meeting's creator. It does not cover failure modes or what the call returns, keeping it off 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?

Purpose and identity are front-loaded, and the permission gate plus the listen hand-off are packed into three tight sentences with no filler. Minor cost: the nested quoting around "<your name>" is slightly awkward to parse.

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 tool with no annotations and no output schema, the description covers identity, announcement, removability, eligibility, and the required follow-up call. What remains unsaid is the result of the call and error behavior, a small residual 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 100% and the single `meeting` parameter is fully documented there, including the code format and link alternative. The description adds no extra semantics about that parameter, so the baseline 3 applies.

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

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

States a specific verb and resource ("Join a TeamMeet call") plus the identity it assumes ("as your own agent — '<your name>'\''s Claude"), which is enough to distinguish it from start_meeting and send_notetaker without opening any schema. It also explicitly names the follow-up sibling (listen).

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

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

Gives a clear precondition ("You can only join a call the person this connector belongs to is in (signed in) or started") and a next step ("Then call listen to hear it"). It does not explicitly say when to use start_meeting instead, so it falls just short of full alternative routing.

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

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

With no annotations, the description carries the full burden and does: it discloses blocking semantics (returns as soon as there is something, or after wait_seconds), a hard presence rule (90s idle = leave), and a notable data-quality trait (each microphone transcribed separately, so speakers are ground truth).

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

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

Front-loaded with the core purpose and no filler, but the first sentence is heavily loaded with clauses, packing three payload types plus a data-provenance note; splitting it would improve scanability without losing content.

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

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

There is no output schema, yet the description enumerates what comes back (transcript lines with speaker, chat messages, tasks) and the continuation field, so the agent can act on the response. The gap is the undocumented `meeting` identifier and what happens when nothing was joined or the call ended.

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 adds cross-call meaning for `since` ("pass back the 'next' value") that the schema alone doesn't make obvious as a continuation token loop, and schema already documents `wait_seconds`. The `meeting` parameter has no description in either schema or description (67% coverage), so the identifier's expected form is unexplained.

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

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

States a specific verb+resource: blocking wait for new activity (transcript lines, chat, tasks) inside a call you joined. That clearly distinguishes it from the sibling read tools get_transcript/get_notes, which fetch static history, and from send_message/speak, which write.

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?

"Keep calling it to stay in the call; you leave after 90 seconds without one" tells the agent both the polling pattern and the consequence of stopping. It does not explicitly name when to prefer get_transcript for backfill, so it falls short of full alternative routing.

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

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

With no annotations, the description carries the full burden, and it does disclose two non-obvious behaviors: the listing is key-scoped and restricted to currently running meetings, and each entry includes a participant count. It stops short of stating what identifying fields are returned (e.g. meeting IDs) or whether results are capped.

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 the verb and the scoping constraint front-loaded and zero filler. Nothing could be removed without losing 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?

There is no output schema, so the description is responsible for describing the return shape. It gives the participant count but not the identifier an agent would need to feed into join_meeting, hand_off, or get_transcript, leaving a gap for a list tool whose whole purpose is to yield follow-up handles.

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 has nothing to explain and the baseline is 4. The description correctly describes a no-argument listing rather than hinting at filters that do not 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?

A specific verb (List) plus resource (meetings) with an explicit scope: only meetings 'this key started' that are 'still running.' That scope naturally separates it from list_recordings (past recordings) and join_meeting/start_meeting (session actions) without having to name them.

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

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

The 'still running' qualifier implies the tool is for checking active sessions rather than history, which loosely points an agent toward list_recordings for past data. However, no alternative is named and no exclusion or precondition is stated, so the routing is inferred rather than instructed.

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

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

With no annotations, the description does carry useful behavior: results are permission-scoped to the key ('this key can see'), sorted newest-first, and include share links — real information beyond the schema. However, it says nothing about pagination, result limits, or whether share links are publicly accessible, which matter for a listing tool.

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

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

A single front-loaded sentence that packs scope, ordering, and return content with zero filler. Every clause earns its place.

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

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

For a simple read-only list with no output schema, stating ordering and return content covers a lot, but the purpose of the 'meeting' parameter and any pagination behavior remain unaddressed, leaving the caller to guess on the one input it has.

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% for the single 'meeting' parameter, and the description never explains it — whether it's an ID filter, a name, or a scope restriction. The description therefore fails to compensate for the undocumented parameter.

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

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

States a specific verb+resource ('Recordings ... list') with scope ('this key can see'), ordering ('newest first'), and return payload ('share links'). It's distinguishable from list_meetings by naming recordings rather than meetings, though it doesn't explicitly reference the recording-vs-meeting distinction.

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

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

No statement of when to use this versus list_meetings, get_transcript, or get_notes, and no mention of what happens with or without the optional 'meeting' argument. The agent must infer the scoping behavior entirely.

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

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

With no annotations, the description carries the full burden. It does useful work by disclosing the identity scoping ('the person this TeamMeet connector belongs to') and the ordering behavior ('Open ones first'), which implies a read operation. But it never confirms read-only status, says nothing about result volume, pagination, or whether the default set excludes finished items — the last point is left to the schema.

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

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

Three short clauses, purpose front-loaded, with the sibling routing at the end where it belongs. The em-dash aside about the connector's owner is slightly convoluted but earns its place by establishing the scope of 'you'.

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

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

There is no output schema, and the description compensates well by enumerating the fields each task carries (requester, request, call, status). For a one-optional-boolean list tool this is close to complete; only pagination/volume expectations are unaddressed.

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

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

Schema coverage is 100% and the single `all` parameter is already documented as 'Include finished and declined ones too,' so the schema does the heavy lifting. 'Open ones first' adds ordering flavor but arguably blurs whether open-only is a filter or just a sort, which is exactly what the `all` flag controls.

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 identifies the resource precisely — action items handed to the connector's owner — and enumerates what each carries (who asked, what they asked for, which call, current status), which clearly separates it from siblings like get_transcript or list_meetings. It loses a point because the verb is never stated plainly; 'what your calls have handed to you ... to do' requires the agent to infer 'list my tasks'.

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?

'Open ones first' signals the default ordering/priority, and 'Use get_task for the whole of one' explicitly routes the agent to the sibling for detail. What's missing is any statement of when NOT to use it (e.g. for tasks belonging to other people, or for tasks unrelated to calls).

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

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

With no annotations, the description carries the full burden and does well: it discloses the downstream lifecycle (dedupe counting bumps items up the list), the fix path (AI engineer generates a PR, a human reviews before shipping), and the response shape ('the reply carries a link to follow it'). It stops short of stating auth requirements or whether submissions are editable, but the write/approval semantics are unusually well 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?

The workflow and the escalation path are front-loaded, and each sentence adds a distinct fact (dedupe behavior, specificity request, fix routing, return value). It is dense and runs long, but no sentence is purely redundant.

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

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

For a 7-parameter write tool with no output schema and no annotations, the description supplies the missing lifecycle and return-link context, which is what an agent most needs. What remains unaddressed — `kind`/`severity` semantics and the `submit_fix` overlap — are the only meaningful gaps.

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

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

Schema description coverage is 57%, so the baseline is a 3. The description meaningfully explains `fix` (converting to a fix request / PR) and maps naturally onto `page`, `expected` and `actual` ('the page, what you expected, what happened'), but says nothing about the `kind` enum values or the `severity` 1-5 scale, leaving those to the schema alone.

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 ('File') and resource ('something you noticed... a bug, a confusing moment, an idea'), so the agent knows exactly what it does. The main gap is that it never distinguishes itself from the sibling `submit_fix`, even though the `fix=true` path appears to overlap directly with that 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?

It gives content guidance ('Be specific: the page, what you expected, what happened') and a clear condition for `fix=true` ('when the person wants the platform itself changed'). However, it offers no routing against `submit_fix`, no guidance on choosing between `kind` values, and no exclusions, so usage is implied rather than fully specified.

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

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

With no annotations, the description does carry real behavioral weight: it discloses that the message is public ('everyone in the room sees it') and that authorship is attributed to this agent under its own name. It says nothing about prerequisites (must be in the meeting), rate limits, persistence, or failure modes for a write operation.

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

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

Two short sentences, zero filler, with the core action front-loaded and the visibility consequence placed second where it belongs.

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

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

For a two-parameter write tool with no annotations and no output schema, the description covers what happens but not what is required to call it successfully — the meeting identifier format and any join/authorization prerequisite are left 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 coverage is 0% — neither parameter has a description — and the description does not compensate. It never clarifies what 'meeting' expects (ID, code, or name) or whether 'text' has length or formatting constraints.

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

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

States a specific verb and target: post a message into the meeting chat, attributed to this agent. It implicitly distinguishes itself from voice-oriented siblings like speak and from send_feedback/send_notetaker by naming 'meeting chat', though it never names an alternative outright.

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

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

Usage is only implied — you use this when you want to say something in a meeting's chat. There is no explicit when-to-use versus speak (voice) or send_feedback, and no stated prerequisite such as having joined the meeting first.

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

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

No annotations are provided, so the description carries the full burden and does so well: it discloses that the bot joins as a participant, records, and where the outputs land, plus an authentication prerequisite ('key minted while signed in') and a billing model ('metered in minutes per month by plan'). These are exactly the behavioral facts an agent needs that no structured field supplies.

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

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

Four sentences, front-loaded with the action and platform list, and every sentence contributes a distinct fact (capability, destination, auth, billing). Slight density in the third sentence makes it run together, but there is no filler.

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

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

With no output schema and no annotations, the description compensates by explaining what the tool produces and where. It is nearly complete for a low-parameter dispatch tool, though it says nothing about failure modes (in-call bot rejection, host admission requirements) or whether a call is idempotent, which would matter for retry decisions.

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

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

Schema description coverage is 100%, so all three parameters (url, name, join_at) are already documented with defaults and formats. The description adds no syntax or constraint detail beyond what the schema states. Baseline 3 applies when the schema does the heavy lifting.

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

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

The description opens with a specific verb and product ('Send the TeamMeet notetaker') and names the exact platforms it supports. It goes beyond the name by stating the bot joins as a participant, records, and produces transcript/recap/action items in a specific destination. An agent can immediately tell this dispatches a bot rather than joining as a user.

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 'a meeting you did not host' and 'Needs a key minted while signed in' carve out clear preconditions, and 'Omit to join now' from the schema covers the timing fork. However, it never names the obviously adjacent siblings (join_meeting, start_meeting), so the agent must infer when to use dispatch-a-bot versus joining or starting a meeting itself.

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

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

Since no annotations are present, the description must carry the full burden of transparency. It excels by revealing critical behavioral traits: the input method (spoken through speakers), the logging behavior (joins transcript/on the record), and the social cost (interruptions).

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 highly concise. It is front-loaded, addressing the mechanism of speech and recording, and then concludes with a concise operational guideline.

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

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

Given the low annotation coverage, the description is remarkably complete. It addresses the social impact, the delivery mechanism, and the length constraint, leaving no ambiguity for the AI agent.

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

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

With 50% schema coverage, the description must add value. It does so by providing a crucial semantic constraint on the 'text' parameter: 'Keep it to a sentence or two. Nobody wants to be read a paragraph.' This is valuable social 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 clearly defines the action ('Say something out loud') and the context ('in the meeting'). It distinguishes itself from message-based siblings like 'send_message' by specifying that the input is 'spoken through the room's speakers' and 'joins the transcript'.

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 usage guidelines by advising the agent to 'Use sparingly' and clearly stating the reason: 'this interrupts people.' This acts as a critical 'when-not-to-use' rule.

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

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

With no annotations, the description carries the full burden. It usefully discloses the returned artifact (code + link) and the access model (any browser, no account, no download), but says nothing about permissions, what happens on repeated calls (multiple meetings created?), or whether the caller becomes the host/participant.

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, front-loaded with the action and the return value. Each sentence carries distinct information: what it does, how the link can be shared, and the dependency that matters for callers.

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?

No output schema exists, and the description correctly explains what comes back (code and link) and how it is consumed. For a two-optional-parameter creation tool this is nearly complete, though it omits host/participation semantics that would matter when several meeting tools are available.

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

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

Schema coverage is 100% and the mode enum is documented in depth, including defaults, so the schema does the heavy lifting. The description adds nothing about mode or topics, leaving the baseline score appropriate rather than earning above it.

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

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

States a specific verb and resource ("Start a new meeting") plus the immediate payoff ("get its code and link"). The line "Nobody can join a meeting that was not started this way" implicitly separates it from join_meeting, but the sibling is never named, so the differentiation is inferred rather than stated.

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

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

Gives clear context for when this tool is required: it is the prerequisite for anyone joining, and the resulting link needs no account or download. There is no explicit when-not clause or named alternative such as join_meeting or list_meetings, so it falls short of the 5 bar.

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

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

With no annotations provided, the description carries the burden and discloses the key trait: 'Nothing is applied automatically — a person reviews and merges,' preventing the agent from assuming an auto-merge. It also mandates running and reporting tests. It does not mention permissions or what failure looks like, so it falls short of 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?

Front-loads the purpose before the branching usage, behavior, and precondition. It is dense but every sentence carries information; only minor tightening is possible.

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

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

For a 7-parameter mutation with no annotations or output schema, the description covers purpose, usage branching, human-review behavior, and test reporting. It omits return-value expectations (e.g., a PR link) and the role of 'page', leaving small gaps for a tool of this complexity.

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

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

Schema coverage is 71%, and the description adds real meaning beyond the schema by clarifying the either/or relationship between feedback_id and text, which is not encoded in the schema. It also ties 'tests' to the reporting precondition, though the 'page' parameter is left unexplained in both places.

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

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

States a specific verb and resource: open a pull request carrying a unified diff against the Team Meet source for a fix request. This clearly distinguishes it from siblings like send_feedback (reporting) and send_message (chat), so an agent can select it without opening the schema.

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

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

Explicitly branches usage: give feedback_id to attach to an existing request (naming send_feedback and GET /api/fixes as sources for open requests), or give text to file the request and attach the fix in one step. It also states a precondition (run the touched tests first). Conditions and alternatives are both spelled out.

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

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

With no annotations, the description carries the full burden. It usefully discloses that the originating call sees the status in its chat, but does not cover permissions, idempotency, whether transitions are reversible, or error behavior.

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

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

The description is compact and front-loads the core action before enumerating the status-specific expectations. Its slightly conversational phrasing is purposeful, though not maximally direct.

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 mutation tool with no annotations and no output schema, the description covers the main usage pattern and visibility effect. It still leaves gaps around permissions, status transition rules, and what the caller should expect after the update.

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 75%, and the description adds meaningful semantics beyond the schema: it explains the three status values and when to pair them with a note and links. It clarifies that 'done' should include a short note plus links to what was made, and 'blocked' should explain what is needed from a person.

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 conveys that this tool reports a task's progress by setting it to working, done, or blocked. It distinguishes the action from read-oriented siblings like get_task and my_tasks, though the phrasing is indirect rather than a direct 'updates task status' statement.

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 concrete guidance for each status: working when starting, done with a note and links to produced artifacts, and blocked with what is needed from a person. It does not name alternatives or explicitly say when not to use the tool, so it falls short of full routing guidance.

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