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Close Crm

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

A5/5.0
Behavior5/5

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

The annotations only say readOnlyHint=false, destructiveHint=false, and idempotentHint=false, so the description carries the burden of behavioral detail. It discloses claim_token mechanics for anonymous follow-up, daily rate limits, quota exemption, and the fact that feedback is read by a team and influences roadmap. This goes well beyond the annotations and gives the agent a clear expectation 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.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is dense but every sentence earns its place. It front-loads the core purpose, then logically covers use cases, exclusions, follow-up mechanics, rate limits, and cost. While long, the length is justified by the tool's nuanced edge cases and the absence of structured annotations.

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?

With no output schema, the description must explain return behavior, and it does: filing without an account returns a claim_token, and passing it back later returns status and resolution details. It also covers scope restrictions, message guidance, rate limits, and commercial terms, making it fully self-contained for a low-complexity feedback tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Although the schema already covers 100% of parameters, the description adds substantial semantic value. It explains how to pass claim_token back to read a prior report, instructs users to frame issues in terms of Pipeworx tools/packs rather than pasting end-user prompts, and clarifies the context field's purpose. This enhances the schema rather than merely repeating it.

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.' This clearly distinguishes the tool from siblings like ask_pipeworx and discover_tools, marking it as a feedback/reporting channel rather than an information retrieval 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?

The description explicitly enumerates when to use it: bug reports, feature/data_gap requests, praise, and 'other.' It also gives a clear exclusion: only for tools served by this Pipeworx connection, directing users to file elsewhere for other MCP servers. This is strong when/when-not guidance with actionable alternatives.

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

A3.7/5.0
Disambiguation2/5

Multiple Pipeworx tools overlap significantly (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, entity_profile, compare_entities, recent_changes all query similar data). Close CRM tools are distinct but the overall set mixes two domains, causing confusion.

Naming Consistency2/5

Tool names mix snakes (close_get_lead), lowercase (ask_pipeworx), and descriptive phrases (scan_competitor_ai_presence). No consistent verb_noun pattern across the entire set.

Tool Count2/5

37 tools is excessive for a focused server. The combination of Close CRM and Pipeworx data services creates scope creep; many tools could be separate servers.

Completeness3/5

Pipeworx tools offer extensive data coverage, but Close CRM lacks update/delete operations for leads, contacts, and opportunities, leaving basic CRUD gaps.

Resources