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Osf

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?

Discloses rate limiting (5 per identifier per day), non-quota status, the claim_token workflow, and how the team processes feedback. These details go well beyond the neutral annotations and give the agent a realistic picture of side effects and constraints.

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 average but every sentence carries useful info: purpose, usage, exclusions, workflow, rate limits, and cost. It is front-loaded with the core purpose and stays on-topic, though slightly dense.

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?

Without an output schema, the description adequately explains return behavior (claim_token for unauthenticated filing) and follow-up usage. It covers the tool's full lifecycle from filing to resolution, making it complete for an agent to invoke 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 baseline is 3. The description adds extra semantic value by explaining the claim_token flow (file without account, later pass token to read status) and clarifying that context identifies the relevant tool/pack/vertical. This goes beyond what the schema descriptions provide.

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 states the tool's purpose with a specific verb and resource: 'Tell the Pipeworx team something is broken, missing, or needs to exist.' It clearly distinguishes itself from sibling tools, all of which focus on research or discovery rather than feedback.

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 (bug, feature/data_gap, praise), a clear exclusion (tools from other MCP servers), and practical instructions for using claim_token to follow up. This is textbook usage guidance.

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

A3.5/5.0
Disambiguation2/5

Several tools have near-identical or heavily overlapping purposes: ask_pipeworx and ask_pipeworx_beta are currently identical, ask_pipeworx and validate_claim both answer factual questions, and discover_tools and suggest_questions both surface capabilities. The dense set of Polymarket and entity-research tools further blurs boundaries despite long descriptions.

Naming Consistency3/5

Names are consistently snake_case, but they do not follow a single predictable verb_noun pattern: actionable names like ask_pipeworx, search_projects, and compare_entities mix with noun-style names like polymarket_edges, pipeworx_feedback, and recent_changes. The convention is readable but not uniform.

Tool Count2/5

34 tools exceeds the reasonable scope for a coherent server, and many are near-duplicate variants or members of sprawling tool families (ask_pipeworx variants, multiple Polymarket scanners, several meta/discovery tools). The set would be stronger with consolidation around a smaller number of distinct capabilities.

Completeness1/5

If this server is meant to provide OSF access, the surface is severely incomplete: only search_projects, search_preprints, and get_project exist, with no create/update/delete, file handling, registration, or contributor access. If it is meant to be a broader Pipeworx assistant, the OSF tools are unrelated and the domain is so scattered that coverage is incoherent.

Resources