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Crontab

by io.github.pipeworx-io

Entity Profile

entity_profile
Read-onlyIdempotent

"Tell me about X" / "research Acme" / "brief me on Tesla" / "what does Apple do" / "company profile for Microsoft" / "give me the rundown on NVDA" / "everything you know about $TICKER" — full cross-source profile of a US public company in ONE parallel call. ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view. Fans out across SEC EDGAR, XBRL, USPTO patents, federal contracts (USAspending), FDA-licensed biologics (Purple Book), H-1B hiring (DOL LCA), news and GLEIF, and returns: cik + company_name (+ resolved_from/resolved_to when value was a name); recent_filings (up to 5 with pipeworx://edgar/company/{cik}/filings/{accession} URIs); fundamentals (LATEST 10-K Revenues + NetIncomeLoss + Cash, sorted period_end DESC); patents (USPTO PatentsView API sunset May 2025 — soft-fails until reactivated); federal_contracts (USAspending awards where the company is the recipient); fda_products (FDA-licensed biologics — vaccines, cell/gene therapies — from the Purple Book; a company with only small-molecule/generic drugs will show none here, that is expected, not a failure); hiring (H-1B sponsorship volume + salary range from DOL LCA filings); recent news mentions via GDELT→GNews fallback; LEI via GLEIF. sources_used / sources_failed say which of these actually returned data for THIS company — an empty section is a real "no data", not a bug. Pass a ticker ("AAPL"), zero-padded CIK ("0000320193"), OR a company name ("Moderna") — names now resolve via SEC EDGAR's company-name match; a private company (no CIK/ticker) returns resolved:false with an explicit notes line, not a bare failure. type accepts "company" or "ticker" interchangeably — both take the same value shapes above.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYes"company" or "ticker" — both are accepted and behave identically; `value` can be a ticker, CIK, or company name either way. person/place coming soon.
valueYesTicker (e.g., "AAPL"), zero-padded CIK (e.g., "0000320193"), or company name (e.g., "Moderna") — names resolve via SEC EDGAR company-name match.

TDQS

A4.6/5.0
Behavior5/5

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

The description discloses far more than the annotations: the full fan-out across EDGAR, XBRL, USPTO, USAspending, FDA, DOL, news, and GLEIF; how empty sections and sources_failed are to be interpreted; patent API sunset soft-failure; and private-company resolved:false behavior. This goes well beyond readOnly/openWorld/idempotent hints.

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, but nearly every sentence earns its place by specifying behavior, return fields, or expected edge cases. It is front-loaded with usage examples and the 'ALWAYS PREFER' guidance, though the dense wall of semicolons and parentheticals could be better structured for readability.

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 carries the full burden of explaining return values, and it does so comprehensively: cik, resolved_from/to, recent_filings, fundamentals, patents, contracts, fda_products, hiring, news, LEI, and the sources_used/sources_failed mechanism. It also covers failure semantics such as soft-fail and expected empty sections, making the tool fully invocable without additional lookup.

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?

The schema already covers both parameters at 100%, so the baseline is 3. The description adds valuable nuance beyond the schema, such as zero-padded CIK formatting, interchangeable type handling, name resolution via SEC EDGAR, and the private-company resolved:false outcome, which an agent needs for correct invocation.

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 names a specific action and resource: building a 'full cross-source profile of a US public company' in one parallel call, with concrete example phrasings. It also differentiates from the alternative approach of chaining single-pack SEC/XBRL/news lookups, so an agent can tell what this tool is for.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explicitly says to 'ALWAYS PREFER' this tool over chaining single-pack lookups when a holistic view is requested, and provides query examples. It does not explicitly contrast with siblings like compare_entities or deep_research, but the single-company focus and 'one parallel call' guidance give sufficient contextual direction.

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 tools have overlapping purposes: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all answer factual questions with subtle differences that are not immediately clear. Additionally, five polymarket tools cover similar ground (arbitrage, edges, fill risk, spread), making it hard to pick the right one without reading the full descriptions.

Naming Consistency4/5

Tool names are consistently snake_case and mostly follow a verb_noun pattern (e.g., describe_cron, next_runs, validate_claim). Minor deviations exist (bet_research, entity_profile, pipeworx_trending) but the overall style is predictable and readable.

Tool Count2/5

33 tools is well over the high end for a focused server, and the server name 'Crontab' implies a narrow cron utility while most tools are a broad data-research platform. This mismatch makes the count feel bloated and poorly scoped.

Completeness2/5

For a cron server, the set is severely incomplete: only describe_cron and next_runs exist, with no create/delete/update functionality. For the actual data-research domain, it is rich but lacks clear CRUD coverage for many resources, and the inclusion of unrelated cron/memory tools creates dead ends.

Resources