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Glama

Reactome

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 adds substantial behavioral context beyond the empty annotations: rate-limiting ('5 per identifier per day'), free usage ('doesn't count against your tool-call quota'), the claim_token workflow for tracking fixes, and the team's daily digest process. It also instructs against pasting user prompts, clarifying expected input format. No contradiction with annotations.

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 a single dense paragraph, but every sentence carries essential guidance. While longer than the ideal 2-3 sentences, the content justifies the length due to the tool's nuanced scope, token handling, and rate limits. No redundant filler.

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 feedback-routing tool with no output schema, the description covers all necessary context: purpose, applicable scenarios, exclusions, format expectations, token-based follow-up, rate limits, and quota impact. It fully equips the agent to decide when and how to invoke the tool.

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 enriches the claim_token parameter by explaining the workflow ('Filing without an account returns a claim_token; pass it back later as pipeworx_feedback({claim_token:"pwfb_…"})'), adding meaning beyond the schema's simple description. Other parameters are already well-documented in 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 specific verb and resource: 'Tell the Pipeworx team something is broken, missing, or needs to exist.' It clearly distinguishes this tool from sibling tools by focusing on submitting feedback about Pipeworx tools rather than querying data or 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 usage criteria are 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 for non-Pipeworx tools and directs the agent to file with the appropriate server, including a fallback 'Not sure?' check.

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

B3.1/5.0
Disambiguation2/5

Many tools have overlapping research purposes (ask_pipeworx, deep_research, ask_pipeworx_grounded) and multiple bet-related tools (bet_research, polymarket_arbitrage, polymarket_edges). Reactome-specific tools are few but mixed in with unrelated tools, causing ambiguity.

Naming Consistency2/5

Tool names are inconsistent: some snake_case (ask_pipeworx, deep_research), some camelCase (generate_llms_txt, list_subscriptions), and some mixed (pipeworx_feedback, poly market_arbitrage). No uniform pattern.

Tool Count2/5

35 tools is excessive for a Reactome server, as only a handful are Reactome-specific. Many tools are unrelated (e.g., bet_research, compare_entities), making the tool count feel bloated and unfocused.

Completeness2/5

The Reactome-specific tools cover basic pathway lookups but miss key operations like reactions, complexes, or advanced queries. The server's completeness for the Reactome domain is poor, diluted by many non-Reactome tools.

Resources