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Server Quality Checklist

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  • Latest release: v0.1.0

  • Disambiguation5/5

    Every tool targets a distinct action and resource: auth setup vs. auth check, live session ingestion vs. status, local session listing vs. cloud conference listing, and Meet transcript fetching vs. Drive transcript fetching. The only borderline pair is list_sessions and list_recent_conferences, but their descriptions clearly separate local storage from the Meet REST API.

    Naming Consistency5/5

    All tools use a consistent meet_ prefix followed by verb_noun names in snake_case, such as check_auth, start_session, ingest_chunk, list_sessions, fetch_google_transcript, and export_minutes. There are no mixed casing styles, vague generic verbs, or unexpected naming deviations.

    Tool Count5/5

    With 11 tools, the set is well-scoped for a Google Meet transcription and minutes-generation server. Each tool covers a meaningful step in the workflow without redundancy or unnecessary bloat.

    Completeness4/5

    The core workflow is well covered: auth, live ingestion, status, listing, transcript retrieval from both Meet and Drive, synthesis, and export. Minor gaps exist around session lifecycle management—there is no explicit stop/end session, delete session, or raw transcript export—but agents can work around these by using synthesize and export.

  • Average 3.4/5 across 11 of 11 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 2 commits in the last 12 weeks
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI status not available
  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

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      "$schema": "https://glama.ai/mcp/schemas/server.json",
      "maintainers": [
        "your-github-username"
      ]
    }

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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

  • Behavior2/5

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

    With no annotations provided, the description carries the full burden of behavioral disclosure. It states that the tool queries an API, implying a read operation, but it does not mention auth requirements, pagination behavior, rate limits, or any other side effects. This is minimal transparency for an API-backed tool.

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

    Conciseness5/5

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

    The description is a single sentence that clearly states the action, the API version, and the object. It is front-loaded and contains no filler, making it appropriately concise for a simple list operation.

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

    Completeness3/5

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

    The tool is simple, has an output schema, and only one optional parameter, so the description is mostly sufficient for basic invocation. However, it lacks any mention of auth prerequisites or when to choose this over related Meet tools, leaving some contextual gaps.

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

    Parameters2/5

    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 compensate by explaining the page_size parameter. The parameter is simple and self-explanatory from its name and default value, but the description adds no semantic meaning beyond what the schema already provides.

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

    Purpose4/5

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

    The description uses a specific verb ('Queries') and a specific resource ('Google Meet REST API v2') with a clear object ('recent conference records'). It is not a tautology, but it does not distinguish itself from the sibling tool meet_list_sessions, so it stops short of a perfect score.

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

    Usage Guidelines2/5

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

    There is no guidance about when to use this tool versus alternatives like meet_list_sessions or meet_fetch_google_transcript. The description gives no context about prerequisites such as authentication being set up or when a caller should choose this over a sibling.

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

  • Behavior2/5

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

    With no annotations, the description must carry the full behavioral burden. It does disclose a read-only operation and local scope, but it does not explain how the 'limit' parameter interacts with the claim of listing 'all' sessions, nor does it mention auth requirements or session-state filtering.

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

    Conciseness5/5

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

    The description is a single, front-loaded sentence with no wasted words. It efficiently conveys the core action and resource.

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

    Completeness3/5

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

    For a simple one-optional-parameter tool with an output schema, the description is minimally adequate. However, it is incomplete in distinguishing this tool from meet_list_recent_conferences and in clarifying the behavior of the limit parameter relative to 'all' sessions.

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

    Parameters2/5

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

    Schema description coverage is 0%, and the description never mentions the only parameter, limit. While 'limit' is fairly self-explanatory from the schema title and default value, the description's use of 'all' creates ambiguity about whether the limit actually truncates the result set.

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

    Purpose4/5

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

    The description uses a specific verb ('Lists') and clearly identifies the resource: locally stored meeting sessions with metadata. It is understandable on its own, but it does not differentiate itself from the sibling tool meet_list_recent_conferences, which may appear similar to an agent.

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

    Usage Guidelines2/5

    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 such as meet_list_recent_conferences. The phrase 'locally stored' hints at a scope distinction, but no explicit context, exclusions, or conditions are provided.

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

  • Behavior2/5

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

    With no annotations provided, the description carries the full burden. It discloses a side effect ('parses them into a durable session') but does not state authentication prerequisites, whether a session is created or updated, or the lifecycle impact. The read-then-persist behavior is only partially transparent.

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

    Conciseness5/5

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

    A single tight sentence that leads with the main action and resource. No filler; every clause adds information about the tool's behavior.

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

    Completeness2/5

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

    Despite an output schema, the description omits prerequisites (auth/session existence) and parameter semantics, and only vaguely explains the 'durable session' side effect. For a tool with no annotations and a low-coverage schema, this is not complete enough to invoke reliably in all cases.

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

    Parameters2/5

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

    Schema description coverage is 0%, so the description must clarify the two parameters. It does not explain how file_id_or_query behaves when it is a query versus an ID, and the optional title is left entirely ambiguous. The word 'Finds' provides only a weak hint.

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

    Purpose4/5

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

    The description identifies a specific verb sequence ('finds and reads... parses') and a concrete resource: Google Meet transcripts auto-saved in Google Drive. It is clear enough to distinguish from siblings like meet_fetch_google_transcript, though it does not explicitly name the distinction.

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

    Usage Guidelines3/5

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

    The source ('auto-saved in Google Drive') and destination ('durable session') imply when to use it, but the description gives no explicit guidance on when not to use it or what alternative to choose, such as meet_fetch_google_transcript or meet_start_session.

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

  • Behavior2/5

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

    With no annotations provided, the description carries the full burden of behavioral disclosure. It does add one meaningful behavior, 'automatically flushes to disk immediately', indicating persistence, but it omits critical operational details such as authentication requirements, failure behavior when no active session exists, whether chunks are appended, and whether calls are idempotent.

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

    Conciseness5/5

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

    The description is exactly two sentences with no filler. It front-loads the primary purpose and then adds a concise behavioral detail about immediate disk flushing; every word earns its place.

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

    Completeness2/5

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

    For a write operation with no annotations and 0% parameter documentation, the description is too thin to fully prepare an agent. It does not explain how to supply relative_seconds, what speaker values should look like, whether an active session must already exist, or what happens if the session is invalid.

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

    Parameters2/5

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

    Schema description coverage is 0%, so the description must compensate for undocumented parameters. It indirectly maps 'spoken line/chunk' to the text parameter and 'active session' to session_id, but it never explains the speaker or relative_seconds parameters, their formats, or semantics.

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

    Purpose4/5

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

    The description uses a specific verb ('ingests'), a specific resource ('live spoken line/chunk'), and a clear context ('active session', 'real-time'), which makes the tool's purpose unmistakable. It is distinguishable from sibling tools like fetch_google_transcript or export_minutes by its ingestion focus, though it does not explicitly name those alternatives.

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

    Usage Guidelines3/5

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

    The phrase 'live spoken line/chunk into an active session in real-time' implies it should be used during an ongoing meeting, when streaming spoken content into the session. However, it gives no explicit guidance on when to prefer this tool over alternatives, nor does it state when not to use it.

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

  • Behavior2/5

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

    No annotations are provided, so the description carries the full behavioral burden. It discloses read-only intent via 'Retrieves' and lists response contents, but omits auth expectations (significant given meet_check_auth/meet_setup_auth siblings), the precondition that the session must be active/live, and error behavior for stale or nonexistent sessions.

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

    Conciseness5/5

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

    One efficient sentence with the verb and resource front-loaded, followed by a tight enumeration of response fields. No filler; every element names a distinct piece of returned data and earns its place.

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

    Completeness3/5

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

    An output schema exists, so return values are covered elsewhere and the field enumeration is a helpful bonus. The tool is low-complexity (2 params, 1 required), but the description fails to state the live-session prerequisite and session_id provenance, both of which an agent needs to call it correctly without erroring.

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

    Parameters2/5

    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 but only weakly does. 'Recent utterances' loosely hints at recent_lines' purpose, yet session_id provenance is never explained — an agent cannot tell it should come from meet_start_session or meet_list_sessions — and the mapping from recent_lines to the returned utterances is only implicit.

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

    Purpose5/5

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

    Specific verb ('Retrieves'), clear resource ('live status of a meeting'), and an explicit enumeration of the returned data (duration, word count, utterance count, speaker breakdown, recent utterances). The 'live status' framing distinguishes it from the transcript-fetching siblings (meet_fetch_google_transcript, meet_fetch_drive_transcript) and session-management tools without needing to open their schemas.

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

    Usage Guidelines2/5

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

    No guidance on when to use this tool versus alternatives. The 'live' qualifier implies it is meant for in-progress meetings, but there is no explicit statement of when to prefer it over transcript-fetching or session-list tools, and no mention that a session must already exist before calling.

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

  • Behavior4/5

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

    No annotations are provided, so the description carries the full behavioral burden — and it delivers meaningfully. It discloses durability, append-only disk buffering, a 3+ hour capacity, and the specific failure modes it prevents (memory exhaustion, data loss). It does not disclose idempotency, auth requirements, or what happens if called twice with the same meeting_code, but the core behavior is well covered.

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

    Conciseness5/5

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

    Two sentences with the main action front-loaded and every clause earning its place. The durability guarantee and the 3+ hour claim are packed efficiently without filler or repetition of the tool name.

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

    Completeness2/5

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

    An output schema exists, so return values are handled, and the description covers core behavior well. However, with 0% parameter coverage, no annotations, and no positioning relative to siblings — especially the auth tools and meet_ingest_chunk — the agent lacks enough context to invoke this tool correctly within the larger meeting workflow.

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

    Parameters1/5

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

    Schema description coverage is 0%, and the description mentions none of the three parameters (title, source, meeting_code). The unexplained defaults — including the Vietnamese default 'Cuộc họp trực tiếp' and source='live_stream' — leave an agent without any basis for choosing parameter values or understanding what meeting_code is for.

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

    Purpose5/5

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

    The description uses a specific verb and resource — 'Starts a new durable meeting session' — with 'durable' and 'append-only disk buffering' adding discriminating detail. The action clearly contrasts with sibling tools that list, fetch, ingest, synthesize, or export, so an agent can tell them apart without opening schemas.

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

    Usage Guidelines2/5

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

    The description gives no guidance on when to use this tool versus alternatives, and no prerequisites are stated. Given siblings like meet_check_auth and meet_setup_auth, an agent is left to guess whether authentication must happen first. The tool's position in the session pipeline (start → ingest → synthesize → export) is never indicated.

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

  • Behavior3/5

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

    With no annotations provided, the description carries the behavioral disclosure burden. It does disclose the external API source, participant-name resolution, and the non-obvious side effect of creating a local durable session. However, it does not mention authentication prerequisites, idempotency, or failure behavior, which are relevant for an external API call.

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

    Conciseness5/5

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

    A single dense sentence with no filler, front-loaded with the main action and followed by useful secondary behaviors. Every clause earns its place.

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

    Completeness3/5

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

    The description covers the main input, source, resolution behavior, and side effect, and the output schema makes return values unnecessary to describe. Gaps remain: no stated requirement for prior authentication/setup and no semantics for the optional title parameter, leaving the tool slightly incomplete for correct invocation.

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

    Parameters2/5

    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 gives some meaning to conference_record_id by saying 'for a given conference record,' but it entirely omits the optional title parameter, leaving its purpose and default behavior unexplained.

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

    Purpose5/5

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

    The description states a specific action (fetches full transcript entries), a specific source (Google Meet API v2), and a target input (a given conference record). It also clearly distinguishes itself from the Drive-transcript sibling by naming the Meet API source.

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

    Usage Guidelines3/5

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

    The description implies when to use the tool: when a conference_record_id is available and full transcript entries plus participant names are needed. However, it does not explicitly mention alternatives such as meet_fetch_drive_transcript or any conditions for avoiding this tool.

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

  • Behavior3/5

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

    With no annotations provided, the description carries the full burden of behavioral disclosure. It does state the transformation ('synthesizes into a report') and lists the output sections, which tells the agent what to expect. However, it does not disclose whether the operation is read-only, requires authentication, is asynchronous, or has prerequisites like a completed/ingested session.

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

    Conciseness5/5

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

    The description is a single sentence that leads with the core action and packs the output components into a list. The final clause about AI prompts adds non-obvious value. No filler or redundancy.

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

    Completeness3/5

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

    The tool has a simple one-parameter schema and an output schema, so the description does not need to enumerate return values. However, it omits call preconditions: whether the session must be finished, ingested, or whether '3-hour+' is a hard requirement. Auth and status could have been clarified, leaving the agent to infer setup steps from sibling tools.

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

    Parameters3/5

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

    The input schema has one parameter (session_id) with no description, and schema coverage is 0%. The description references 'meeting session' twice, which connects session_id to a meeting session, but it does not specify where to obtain the ID (e.g., meet_list_sessions), its format, or any constraints. Some meaning is added, but not enough to fully compensate for zero schema coverage.

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

    Purpose5/5

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

    The description opens with a specific verb ('Synthesizes') and resource ('a 3-hour+ meeting session'), and details the report components (Timeline Milestones, Decision Log, Action Items Matrix, Participant Analytics). This clearly differentiates it from sibling tools like meet_fetch_*_transcript and meet_export_minutes, which have different actions.

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

    Usage Guidelines3/5

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

    The description implies the tool should be used when a comprehensive minutes report is needed from a long meeting session, but it does not provide explicit guidance on when to prefer it over meet_export_minutes, fetch transcripts, or other alternatives. No when-not conditions or alternative tool names are mentioned.

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

  • Behavior3/5

    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 filesystem side effect (writes local documents to the exports directory) and adds useful format traits (HTML is print/PDF ready, JSON is structured). However, it omits what happens when a session has no synthesized minutes, overwrite behavior, and auth prerequisites.

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

    Conciseness5/5

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

    A single, front-loaded sentence with the verb 'Exports' leading. Every clause earns its place: resource, three formats with useful traits, and the destination. There is no repetition of schema fields or filler.

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

    Completeness4/5

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

    For a simple two-parameter tool with an output schema covering return values, the description covers the essentials: what is exported, available formats, and where files land. Remaining gaps are moderate given zero annotations and schema descriptions - the unstated prerequisite of meet_synthesize_meeting, exact format string values, and auth/overwrite behavior.

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

    Parameters3/5

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

    Schema coverage is 0%, so the description must compensate. It adds real meaning to the format parameter by enumerating Markdown/.md, HTML/.html, and JSON/.json, and it scopes session_id to a session whose minutes were synthesized. Yet it never gives the exact accepted string values for format or defines the session lifecycle relationship beyond the adjective 'synthesized.'

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

    Purpose5/5

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

    The description uses a specific verb and resource combination ('Exports the synthesized meeting minutes') plus concrete output formats and a destination. Among the siblings, none perform exports, so this tool is inherently distinguished from meet_synthesize_meeting (which produces minutes) and the fetch/list tools.

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

    Usage Guidelines3/5

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

    Usage context is implied rather than explicit: calling the minutes 'synthesized' signals the prerequisite of meet_synthesize_meeting, but the description never names the sibling, states 'run after synthesis completes,' or mentions auth requirements via meet_check_auth. No exclusions or alternative routing are given.

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

  • Behavior4/5

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

    With no annotations available, the description carries the disclosure burden and does so meaningfully: it explicitly says the tool initiates an OAuth flow, runs in the browser, authorizes three specific API scopes, and needs a credential file. It does not mention token persistence or blocking behavior, but the browser-flow framing is sufficiently transparent for the core operation.

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

    Conciseness5/5

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

    A single sentence packs the action, scope, and prerequisite with no filler. The key behavior is front-loaded, and every phrase earns its place.

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

    Completeness4/5

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

    For an interactive setup tool, the description covers the action, authorized scopes, browser behavior, and required credential file. Since an output schema exists, explaining return values is not the description's responsibility. The main missing context is a note about headless environments or open_browser=false, but the definition is otherwise nearly complete.

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

    Parameters3/5

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

    Schema description coverage is 0%, and the only parameter is open_browser. The description's 'in the browser' reinforces that parameter's meaning, but it does not explain the behavior when open_browser=false or why an agent would set it that way. For a single simple boolean, this partial compensation is adequate but not detailed.

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

    Purpose5/5

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

    The description states a specific verb ('Initiates') and names the exact resource: the Google OAuth 2.0 flow, scoped to Meet, Drive, and Calendar access. This clearly distinguishes it from the sibling tools, none of which perform auth setup.

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

    Usage Guidelines3/5

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

    The description gives a hard prerequisite: credentials.json from Google Cloud Console. It implies this is the setup step before other Meet tools, but it never explicitly says when to run it, when not to, or how it relates to meet_check_auth.

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

  • Behavior4/5

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

    No annotations are provided, but the verb 'Checks' clearly conveys a read-only inspection with no mutating side effects. It also enumerates the specific aspects inspected: status, tokens, credentials, and API scopes. This is sufficient behavioral disclosure for a simple status-checking tool.

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

    Conciseness5/5

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

    The description is a single, front-loaded sentence with no filler. Every element earns its place by specifying exactly what the tool checks.

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

    Completeness4/5

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

    For a tool with no parameters, an output schema, and a simple read-only purpose, this description provides adequate context for an agent to select and invoke it. The only gap is explicit guidance about when to prefer this over related auth tools.

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

    Parameters4/5

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

    The tool has zero parameters and the schema coverage is 100%, so there is no parameter information for the description to add. The description appropriately omits parameter details because none exist.

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

    Purpose5/5

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

    The description uses a specific verb ('Checks') and identifies a clear resource: Google OAuth2 authentication status, tokens, credentials, and API scopes. This distinguishes it from its sibling meet_setup_auth, which is about establishing authentication rather than checking it.

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

    Usage Guidelines3/5

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

    The description implies this tool should be used when an agent needs to verify the current OAuth2 authentication state before proceeding with Google Meet operations. However, it does not explicitly state when to use it versus alternatives like meet_setup_auth or provide exclusions.

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

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