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Funcheap

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?

Beyond the neutral annotations (all false), the description discloses key behaviors: the no-account claim_token flow, passing the token back to check status, rate limiting ('5 per identifier per day'), cost ('free; doesn't count against your tool-call quota'), and the team's daily digest process. This is substantial operational context the annotations do not capture.

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 long (~250 words) but justified by the tool's complexity: multiple event types, cross-server disambiguation, claim_token flow, and rate limits. It is front-loaded with a clear purpose statement. Some redundancy like 'signal directly affects roadmap' could be trimmed, but each sentence adds needed operational context.

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 tool with 4 parameters (1 nested, 0 required), no output schema, and neutral annotations, the description covers all essential context: what it does, when to use/not use, the async token-based follow-up flow, rate limits, cost, and how feedback is consumed. The agent can confidently decide when to invoke this tool and what to pass.

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% with already-detailed parameter descriptions. The main description adds extra value by explaining the claim_token workflow in context ('Filing without an account returns a claim_token; pass it back later...'), clarifying message style ('1-2 sentences typical' reinforces the schema), and emphasizing the need to reference Pipeworx tools/packs rather than pasting end-user prompts. This exceeds the baseline for high coverage.

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+resource: 'Tell the Pipeworx team something is broken, missing, or needs to exist.' It clearly differentiates from sibling tools like ask_pipeworx (which are Q&A/research tools) by establishing this as the feedback channel for the Pipeworx tool suite.

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 use cases ('Use when a tool returns wrong/stale data... feature/data_gap... praise') and exclusions ('ONLY for tools served by this Pipeworx connection — if the tool came from a different MCP server... file it with that server instead'). Also includes a helpful 'Not sure?' disambiguation for identifying Pipeworx tools.

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

A4.1/5.0
Disambiguation4/5

Most tools are distinct (event search, subscriptions, memory, Polymarket arbitrage, data lookups), but ai_visibility_check, scan_competitor_ai_presence, bet_research, polymarket_edges, and polymarket_arbitrage have overlapping purposes around competitive research and prediction-market edge-finding. The detailed descriptions disambiguate them, though an agent could confuse polymarket_edges with polymarket_arbitrage.

Naming Consistency4/5

Tool names are mostly descriptive and consistent: search_events, event, categories, tags are aligned; ask_pipeworx, compare_entities, entity_profile follow a similar pattern. However, polymarket_* tools have an odd mix of `polymarket_arbitrage`, `polymarket_fill_risk`, and `polymarket_edge_tracker`, and discover_tools/recent_alerts/recent_changes are consistent, mostly. Naming is quite consistent overall with minor deviations.

Tool Count3/5

At 35 tools, the count is heavier than typical MCP servers, but it reflects a broad service (Funcheap data + Pipeworx data platform + pred markets). Still, plenty of tools serve the same primary purpose (polymarket_, ask_pipeworx variants) so some pruning would improve the surface.

Completeness4/5

The surface appears complete for its domain: search/retrieve events, category/tag navigation, memory, subscriptions (create/list/cancel/pull), data lookups, entity resolution, comparisons, profiles, edge scanning, and feedback. Minor gaps include no direct 'update' on events (but events are static), and no pricing fetch tool separate from event text, though body text covers it.

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