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Glama

Oeis

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

A4.5/5.0
Behavior4/5

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

Annotations are all false, so the description carries the burden of disclosure. It adds useful behavior: rate-limited to 5 per identifier per day, free, doesn't count against tool-call quota, returns a claim_token for later lookup, and team reads digests daily. This goes well beyond the annotations, though it doesn't specify any side effects beyond submitting a report. A small gap is what constitutes an 'identifier' for rate limiting, but overall it's transparent.

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 longer than the high-calibration example but every sentence adds value: purpose, use cases, exclusions, claim-token flow, rate limits, and roadmap impact. It is front-loaded with the core action and uses a logical flow. However, it could be slightly tighter; the 'Not sure?' sentence about tool names could be integrated elsewhere. Still, it's concise relative to its content density.

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?

Given there is no output schema, the description covers the expected outputs (claim_token, later status) and explains the broader context (daily digest, roadmap signal, rate limit). It also clarifies what not to include (end-user's prompt) and how to identify Pipeworx tools. This is complete enough for a feedback tool, though a note about what happens after filing (e.g., whether there is a confirmation) would round it out.

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 baseline is 3. The description adds workflow context for the claim_token parameter ('pass it back later as pipeworx_feedback({claim_token:"pwfb_…"}) to read whether it was fixed') and advises on how to write the message ('Describe the issue in terms of Pipeworx tools/packs — don't paste the end-user's prompt'). This enhances the parameter semantics beyond the schema's individual field descriptions.

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 siblings by scoping it to feedback about Pipeworx tools and explicitly excluding tools from other MCP servers, which differentiates it from every sibling tool.

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?

Provides 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 gives a direct exclusion criterion: 'if the tool came from a different MCP server... file it with that server instead.' This is textbook usage guidance with alternatives listed.

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

A4/5.0
Disambiguation4/5

Most tools have distinct purposes, but there is some overlap, especially among ask_pipeworx variants (ask_pipeworx, ask_pipeworx_grounded, ask_pipeworx_beta) and prediction market tools (polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, polymarket_fill_risk, polymarket_kalshi_spread, bet_research). While descriptions help distinguish them, the boundaries are somewhat fuzzy.

Naming Consistency2/5

Naming conventions are inconsistent. Some tools use verb_noun (search_sequence, compare_entities), others use noun_verb (entity_profile, recent_changes), and some have prefixes (pipeworx_feedback, pipeworx_trending) while others do not (remember, forget). There is no uniform pattern, which reduces predictability.

Tool Count2/5

The server name 'Oeis' suggests a focus on integer sequences, but only 2 of 33 tools are OEIS-related. The remaining tools cover a vast array of unrelated domains (data retrieval, prediction markets, memory, subscriptions). This mismatch between name and scope makes the tool count feel excessive and poorly scoped.

Completeness4/5

Within the broad domains covered, the tool surface is quite complete. For memory, there are remember/recall/forget; for subscriptions, subscribe/unsubscribe/list_subscriptions/recent_alerts; for data retrieval, multiple entry points. Minor gaps exist, such as lack of OEIS sequence contribution tools, but overall the set is well-rounded.

Resources