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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.

TDQS

A4.8/5.0
Behavior5/5

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

With all annotations false (no readOnly, idempotent, etc.), the description carries the full burden and fully delivers. It discloses the claim_token flow, state that it is 'Rate-limited to 5 per identifier per day,' and clarifies it is 'Free; doesn't count against your tool-call quota.' It also reveals that the team reads digests daily.

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 every sentence serves a distinct purpose: purpose, when-to-use, exclusions, message guidance, claim_token, rate limit, and cost. It front-loads the primary purpose but is more verbose than the two-sentence ideal; still, no content is wasted.

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?

No output schema exists, and the tool has nested objects and two distinct operation modes (submit feedback and check status). The description explains both modes, the optional context object, the claim_token flow, rate limits, and what happens after filing. It is complete enough for an agent to use correctly.

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 meaning by advising message formatting: 'Describe the issue in terms of Pipeworx tools/packs — don't paste the end-user's prompt.' It also clarifies claim_token usage beyond the schema by describing the dual-mode behavior (submit vs. read reply).

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 and resource: 'Tell the Pipeworx team something is broken, missing, or needs to exist.' It clearly distinguishes the tool from siblings by being the dedicated feedback channel, with enumerated feedback types (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?

The description gives explicit when-to-use guidance: '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 provides an explicit when-not-to-use and alternative: 'if the tool came from a different MCP server... file it with that server instead.'

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

Multiple tools have overlapping purposes, notably ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded which are near-identical in function. The polymarket_* family also has several members with closely related scopes, and the large number of data-query tools makes it hard to choose the right one without careful reading.

Naming Consistency3/5

All names use snake_case, but the pattern is inconsistent: some are verb-first (list_subscriptions, validate_claim), others are noun-first (entity_profile, bet_research), and proper-noun prefixes like pipeworx_ and polymarket_ are used liberally. The gitlab_* tools follow a clear verb_noun pattern, but the rest of the set is mixed.

Tool Count2/5

With 36 tools, the server is overloaded, especially given that only 5 are GitLab-related while the rest are a sprawling data-access toolkit. Many tools could be consolidated (e.g., the ask_pipeworx variants), and the count exceeds what is reasonable for a focused GitLab server.

Completeness2/5

For a server named Gitlab, the coverage is severely incomplete: only list/get operations exist for projects, issues, and MRs, with no create, update, or delete capabilities. The broader data tools are more complete, but the nominal purpose of the server is clearly not fulfilled.

Resources