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Glama

Take The Meeting

by io.github.pipeworx-io

Send Pipeworx Feedback

pipeworx_feedback

Tell the Pipeworx team something is broken, missing, or needs to exist. Use when a tool returns wrong/stale data (bug), when a tool you wish existed isn't in the catalog (feature/data_gap), or when something worked surprisingly well (praise). ONLY for tools served by this Pipeworx connection — if the tool came from a different MCP server in your client (another vendor's Gmail, Splunk, Slack, etc. connector), we cannot fix it and reporting it here only delays you; file it with that server instead. Not sure? Pipeworx tool names are the ones this connection lists. Describe the issue in terms of Pipeworx tools/packs — don't paste the end-user's prompt. Filing without an account returns a claim_token; pass it back later as pipeworx_feedback({claim_token:"pwfb_…"}) to read whether it was fixed and what changed. The team reads digests daily and signal directly affects roadmap. Rate-limited to 5 per identifier per day. Free; doesn't count against your tool-call quota.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNobug = something broke or returned wrong data. feature = a new tool or capability you wish existed. data_gap = data Pipeworx does not currently expose. praise = positive note. other = anything else.
contextNoOptional structured context: which tool, pack, or vertical this relates to.
messageNoYour feedback in plain text. Be specific (which tool, what error, what data was missing). 1-2 sentences typical, 2000 chars max.
claim_tokenNoRead the reply to a report you filed earlier: pass the `pwfb_…` token that filing returned, with no other arguments. Returns the status and, once resolved, what actually changed.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed2 schema fields changed
    • addedInput schema / properties / claim_token
      Added value: +{
+  "description": "Read the reply to a report you filed earlier: pass the `pwfb_…` token that filing returned, with no other arguments. Returns the status and, once resolved, what actually changed.",
+  "type": "string"
+}
    • removedInput schema / required
      Removed value: -[
-  "type",
-  "message"
-]
  2. Added

TDQS

A4.8/5.0
Behavior5/5

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

Discloses rate limits ('Rate-limited to 5 per identifier per day'), the claim_token flow ('Filing without an account returns a claim_token; pass it back later'), the fact that it is free and doesn't count against tool-call quota, and how the team processes feedback ('reads digests daily and signal directly affects roadmap'). This goes well beyond the sparse annotations (all false) and leaves no ambiguity about side effects or expectations.

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

Conciseness4/5

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

The description is longer than average but every sentence adds critical operational detail (scope, token flow, rate limit, quota). It is front-loaded with purpose and usage, then flows logically into mechanics and constraints. It earns the length, but could be tightened by moving the 'Not sure?' clause earlier—still highly structured.

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

Completeness5/5

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

For a 4-parameter, no-output-schema tool, the description covers all essential context: what to report, what not to report, scope exclusions, token-based follow-up, team workflow, and rate limits. No output schema exists, but the description explains the claim_token return behavior sufficiently. This is complete enough for an agent to invoke the tool correctly and follow up appropriately.

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?

Schema coverage is 100%, so baseline is 3. The description adds meaningful semantics beyond schema: it explains the claim_token round-trip pattern in detail, instructs on message content ('Describe the issue in terms of Pipeworx tools/packs — don't paste the end-user's prompt'), and contextualizes the 'type' enum via the usage examples. Slight deduction because it doesn't directly walk through the nested 'context' object, but the schema already covers that.

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 clear verb+resource: 'Tell the Pipeworx team something is broken, missing, or needs to exist.' It also lists concrete categories (bug, feature/data_gap, praise) and distinct scope (only for tools served by this Pipeworx connection), which clearly distinguishes it from sibling research/subscription tools.

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

Usage Guidelines5/5

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

Explicitly states when to use: 'Use when a tool returns wrong/stale data (bug), when a tool you wish existed isn't in the catalog (feature/data_gap), or when something worked surprisingly well (praise).' It also gives exclusions: if the tool came from a different MCP server, 'file it with that server instead,' and offers a heuristic for uncertainty: 'Pipeworx tool names are the ones this connection lists.'

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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TDQS

A3.7/5.0
Disambiguation3/5

Most tools have distinct, well-documented roles, but the set includes two effectively identical routers (ask_pipeworx and ask_pipeworx_beta, with the latter explicitly matching the former right now) and a dense cluster of six Polymarket tools that an agent must read carefully to choose among. This is more than a minor overlap, though the detailed descriptions prevent it from being complete chaos.

Naming Consistency3/5

Everything is snake_case, which is a plus, but the patterns are inconsistent: some tools are verb_noun (resolve_entity, validate_claim, list_subscriptions), some are noun phrases (entity_profile, bet_research, recent_alerts), some use brand prefixes (ask_pipeworx*, polymarket_*, pipeworx_*), and take_the_meeting_evaluate is a sentence-like outlier. The prefixes do provide grouping, but the naming doesn't give a predictable action structure.

Tool Count2/5

32 top-level tools is above the 25+ threshold and will bloat an agent's tool-selection surface, especially because the server name 'Take The Meeting' suggests a narrow meeting tool while 31 of the tools are unrelated Pipeworx/data features. Even as a broad data-research server, several tools could be collapsed (the ask variants, the Polymarket family), so the count feels inflated.

Completeness2/5

For the purpose implied by the server name and the lone meeting tool, the surface is severely incomplete: there is no way to list or fetch meetings, access calendar/attendee context, or do anything beyond evaluating one set of supplied parameters. For the broad data-research domain that most tools actually serve, the read/research side is rich, but that is a completely different purpose from 'Take The Meeting', leaving the meeting feature as a disconnected dead end.

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