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Glama

Crontab

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?

The description richly discloses behaviors beyond annotations: it returns a claim_token when filed without an account, explains how to later use that token to check status/changes, mentions the 5-per-day rate limit, states it is free, and notes that the team reads digests daily. No annotation contradiction exists.

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 longer than average, but every sentence earns its place: purpose, use cases, exclusion, token mechanics, rate limit, cost, and roadmap impact. It is front-loaded with the core purpose and structured so each sentence adds new, actionable information.

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?

Despite having no output schema, the description covers the key workflow: filing feedback, receiving a claim_token, reading later resolution status, and the rate-limit/free constraints. It is complete for a feedback tool with nested optional context and four parameters, and it clearly communicates the tool's closed-world scope.

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 the baseline is 3. The description adds valuable semantics beyond the schema, especially for claim_token, explaining the token lifecycle and that it should be passed alone. It also gives message-level guidance ('don't paste the end-user's prompt'), though it does not deeply elaborate on every parameter.

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 sibling research/query tools by framing it as feedback to the vendor, not a data lookup or question-answering 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?

Explicit when-to-use guidance is given for each feedback type: bug, feature/data_gap, and praise. It also states when NOT to use it — for tools from a different MCP server, 'file it with that server instead' — and clarifies scope with 'Pipeworx tool names are the ones this connection lists.'

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

A3.6/5.0
Disambiguation2/5

Several tool clusters have blurred boundaries: ask_pipeworx_beta explicitly states it currently matches ask_pipeworx exactly, making them indistinguishable, and the five Polymarket tools (polymarket_edges, polymarket_arbitrage, polymarket_fill_risk, bet_research, polymarket_kalshi_spread) all target prediction-market opportunities with overlapping concerns. The meta-tools (discover_tools, suggest_questions, pipeworx_trending) and entity tools (entity_profile, compare_entities, recent_changes) are better separated by their descriptions, but the identical beta/stable pair alone forces a low score.

Naming Consistency3/5

All tool names use snake_case, but the naming conventions are mixed: some follow verb_noun (describe_cron, next_runs, validate_claim), some are bare verbs (remember, recall, forget), and many are brand-prefixed noun phrases (ask_pipeworx, pipeworx_trending, polymarket_edges, bet_research). The pattern is readable and mostly predictable by prefix/domain, but there is no single consistent convention across the set.

Tool Count2/5

33 tools is above the reasonable threshold for a focused server, and the count is especially disproportionate for a server named 'Crontab': only 2 tools (describe_cron, next_runs) actually deal with cron, while roughly 24 tools are Pipeworx data-query, prediction-market, and memory utilities unrelated to the server's apparent purpose. The bulk of the tool surface feels like it belongs on a different server, making the count mismatched with the stated scope.

Completeness2/5

For a cron-focused server, the surface is incomplete: it can describe cron expressions and compute next runs, but has no tool to create, update, or delete a scheduled cron job — subscribe/unsubscribe manage data-event subscriptions, not cron schedules. The Pipeworx data side is broad (lookup, grounded verification, entity profiles, comparisons, research), but that completeness belongs to a different domain and does not rescue the cron purpose implied by the server name.

Resources