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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

A4.9/5.0
Behavior5/5

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

Annotations are all false and offer little, so the description carries the full burden. It discloses several behavioral traits beyond the schema: filing without an account returns a claim_token for later status retrieval, rate-limit of 5 per identifier per day, free/no quota cost, and that the team reads digests daily. No contradiction with annotations exists.

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 dense but every sentence earns its place. It opens with purpose, then usage, exclusion, content guidance, token workflow, rate limits, and cost—all in a compact, ordered structure. No filler or repetition.

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?

Given the tool's moderate complexity (conditional token flow, exclusion rules, rate limiting), the description covers all necessary aspects: purpose, exact trigger scenarios, boundaries, token handling, and operational details. No output schema exists, but the description sufficiently explains expected return behavior (claim_token and later status).

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 the baseline is 3. The description adds meaningful context for the claim_token parameter (explaining the full workflow: filing returns a token, passing it back later reads status) and for message content (don't paste end-user's prompt). This elevates parameter understanding beyond the schema.

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, specific verb and resource: 'Tell the Pipeworx team something is broken, missing, or needs to exist.' It enumerates exact use cases (bug, feature/data_gap, praise) and clearly differentiates this feedback tool from sibling research/query tools like ask_pipeworx or deep_research.

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?

Explicit when-to-use guidance is provided ('Use when a tool returns wrong/stale data...'), along with a strict when-not-to-use boundary ('ONLY for tools served by this Pipeworx connection') and an alternative action ('file it with that server instead'). It also gives content guidance ('Describe the issue in terms of Pipeworx tools/packs — don't paste the end-user's prompt').

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

B3.4/5.0
Disambiguation2/5

Multiple tools have overlapping purposes, such as ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded all performing similar data lookups. Additionally, many tools focus on prediction markets and arbitrage, which are unrelated to the server's implied Go development domain, causing confusion.

Naming Consistency2/5

Tool names follow inconsistent conventions: some use snake_case (e.g., 'latest_version', 'list_versions'), some use underscores in longer names (e.g., 'ai_visibility_check', 'ask_pipeworx_grounded'), and some use colons in descriptions but not in names. This mix reduces predictability.

Tool Count2/5

With 35 tools, the count is high for a server named 'Pkg Go Dev' that only offers a few Go module-related tools (e.g., get_go_mod, list_versions). The majority are unrelated Pipeworx tools, making the scope mismatched and excessive.

Completeness1/5

The tool set severely lacks coverage for Go development tasks. It only includes basic module lookup tools (version listing, mod retrieval) but misses essential operations like dependency analysis, build commands, or testing. The vast majority of tools cover unrelated domains (prediction markets, company profiles, etc.), leaving the server incomplete for its intended purpose.