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Glama

Cta

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. First observed

TDQS

A4.7/5.0
Behavior5/5

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

With annotations all false, the description carries full weight. It discloses rate limiting ('Rate-limited to 5 per identifier per day'), the claim_token flow ('Filing without an account returns a claim_token; pass it back later...'), and the fact it's free ('Free; doesn't count against your tool-call quota'). It also explains the daily digest and roadmap impact.

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 long but each sentence serves a purpose, and it is well-structured with clear 'Use when', 'ONLY for', 'Filing', and rate-limit info. It could be slightly more concise, but the logical flow makes it easy to scan.

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?

The description covers the two main workflows (new feedback and claim_token lookup) and the return behavior ('read whether it was fixed and what changed'). It lacks an output schema, but the description compensates. Some borderline details like what defines an 'identifier' could be added, but overall it's complete for the tool's purpose.

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 schema already provides 100% coverage, but the description adds value beyond that. For claim_token, it explains the round-trip usage ('pass it back later as pipeworx_feedback({claim_token:"pwfb_…"})'). For message, it adds 'Describe the issue in terms of Pipeworx tools/packs — don't paste the end-user's prompt,' which clarifies expected content beyond the schema's generic text.

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 clearly states the tool's purpose: 'Tell the Pipeworx team something is broken, missing, or needs to exist.' It distinguishes itself from sibling tools by specifying that it is for feedback/reporting issues, not for asking questions (e.g., ask_pipeworx). It also provides concrete use cases (bug, feature/data_gap, praise).

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 tells 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 clear exclusions: 'ONLY for tools served by this Pipeworx connection' and directs users to file with another server for non-Pipeworx tools.

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

A3.6/5.0
Disambiguation2/5

Several tools have heavily overlapping purposes: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, and validate_claim all accept natural-language factual questions, and ask_pipeworx_beta is explicitly described as currently identical to ask_pipeworx. The entity tools (entity_profile, compare_entities, recent_changes, resolve_entity) and the many Polymarket tools also blur together, making misselection likely.

Naming Consistency3/5

Most names are snake_case and readable, with recognizable prefixes like cta_, polymarket_, and ask_pipeworx_. However, conventions are mixed: bare verbs (remember, forget, subscribe), noun-style phrases (entity_profile, bet_research), and variants like ai_visibility_check vs scan_competitor_ai_presence prevent a single predictable pattern.

Tool Count2/5

35 tools is above the comfortable range, and the count is especially mismatched for a server named 'Cta': only 4 tools actually concern Chicago transit, while the other 31 form a general-purpose research, prediction-market, and memory suite. The set feels like multiple unrelated servers merged together.

Completeness2/5

As a CTA server, the surface is notably incomplete: it has bus/train positions and predictions but lacks alerts, service disruptions, route listings, and station/stop metadata. The broader Pipeworx tools are extensive but appear bolted on, so the overall set has no coherent domain against which completeness can be judged.

Resources