Skip to main content
Glama

Osv

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

A4.9/5.0
Behavior5/5

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

Annotations are all false, so the description carries full responsibility. It discloses the claim_token return/read-back flow, the daily rate limit of 5 per identifier, that it's free and doesn't count against tool-call quota, and that the team reads digests daily. This provides rich behavioral context that annotations cannot convey.

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?

Although lengthy, every sentence earns its place: purpose, trigger conditions, exclusion, token mechanics, rate limit, and cost. It is front-loaded with the aim, and dense with actionable information without filler. For this tool's complexity, the length is fully justified.

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 covers purpose, when-to-use, when-not-to-use, token-based follow-up, rate limiting, and cost, while also handling the absence of an output schema by explaining what the tool returns (claim_token). It is thorough enough for an agent to invoke correctly and understand consequences without any further context.

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 value by explaining the claim_token round-trip pattern ('pass it back later as pipeworx_feedback({claim_token:"pwfb_…"}) to read whether it was fixed') and instructing users to frame feedback around Pipeworx tools/packs rather than raw prompts, which complements the schema's per-parameter 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 clear, specific statement: 'Tell the Pipeworx team something is broken, missing, or needs to exist.' It enumerates the feedback categories (bug, feature, data_gap, praise) and clearly differentiates this from sibling tools like ask_pipeworx or subscribe by framing it as the dedicated feedback channel.

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?

Explicitly states when to use the tool ('Use when a tool returns wrong/stale data...'), provides a concrete exclusion ('ONLY for tools served by this Pipeworx connection... file it with that server instead'), and gives practical guidance on what to describe and what to avoid (don't paste the end-user's prompt). This goes far beyond basic usage hints.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Osv toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4/5.0
Disambiguation3/5

Several tools have overlapping purposes: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are very similar, as are the suite of polymarket_* tools. While descriptions help differentiate, an agent may struggle to choose the correct one without careful reading.

Naming Consistency3/5

All tool names use snake_case, but they mix verb-first patterns (ask_pipeworx, compare_entities, validate_claim) with noun-first patterns (bet_research, entity_profile, pipeworx_feedback). This inconsistency makes it harder to guess tool names by convention.

Tool Count3/5

35 tools is on the high side but not unreasonable for a platform covering vulnerability queries, data retrieval, prediction markets, and utilities. However, the server name 'Osv' suggests a narrow focus, making the large count feel bloated.

Completeness4/5

The tool set covers a wide range of operations: querying data, comparing entities, managing user data, monitoring subscriptions, and even onboarding. Minor gaps exist (e.g., no direct API for updating user profiles), but overall it is well-rounded for its domain.

Resources