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Glama

Lemmy

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

A4.8/5.0
Behavior5/5

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

The description discloses behavioral traits well beyond the annotations. It explains the claim_token mechanism, rate limiting ('5 per identifier per day'), that it is free and doesn't count against quota, and that the team reads digests daily. These are valuable operational details not available from annotations (all false) or the schema.

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 fairly long but well-structured and front-loaded. Each sentence carries essential information: purpose in the first sentence, usage conditions, exclusions, token handling, and limits. No sentence is wasted, but the length is more than the minimum needed for a feedback tool.

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?

The description is complete given the complexity. It covers all use cases, the claim_token flow, rate limits, and the connection scope. There is no output schema, but the description clearly states what the tool returns (claim_token and later status). The nested context object is adequately explained in the schema, and the description does not need to repeat it.

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 description coverage is 100%, so the baseline is 3. The description adds meaningful parameter semantics beyond the schema: it instructs to 'describe the issue in terms of Pipeworx tools/packs — don't paste the end-user's prompt' and explains the claim_token usage in detail. This elevates it above baseline, though not to a 5 since schema already covers the basic types.

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 action and target: 'Tell the Pipeworx team something is broken, missing, or needs to exist.' It goes on to specify the exact types of feedback (bug, feature/data_gap, praise) and distinguishes itself from sibling tools by stating it is solely for tools served by this Pipeworx connection, not other MCP servers.

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 (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 a clear exclusion: 'if the tool came from a different MCP server... file it with that server instead.' This fully addresses when to use this tool versus alternatives.

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

Many tools have overlapping purposes: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, and validate_claim all answer factual questions, while bet_research, polymarket_edges, polymarket_arbitrage, and polymarket_fill_risk all analyze prediction markets. The Lemmy tools are distinct from the Pipeworx tools, but within each cluster an agent could easily select the wrong tool despite lengthy descriptions.

Naming Consistency2/5

Naming conventions are mixed: single nouns (post, community, site), verb_noun patterns (list_subscriptions, resolve_entity, generate_llms_txt), and ad-hoc names (ask_pipeworx, forget, recall). There is no consistent verb_noun or noun-only pattern across the set, making it hard to predict tool names.

Tool Count2/5

38 tools is excessive for a server named 'Lemmy' where only 7 tools (comments, communities, community, post, posts, search, site) actually relate to Lemmy. The vast majority of tools belong to an unrelated Pipeworx data platform, creating a severe scope mismatch and making the server feel bloated and unfocused.

Completeness2/5

For the Lemmy domain, the tools cover read-only browsing (list posts, view post, list communities, fetch community, comments, search, site metadata) but completely lack write operations like posting, commenting, voting, or moderation. The Pipeworx tools are extensive but do not compensate for the primary domain's gaps since the server is ostensibly about Lemmy.

Resources