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Glama

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.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed3 schema fields changed
    • changedInput schema / properties / type / description
      Previous value: -"Entity type. Only \"company\" supported today; person/place coming soon."New value: +"\"company\" or \"ticker\" — both are accepted and behave identically; `value` can be a ticker, CIK, or company name either way. person/place coming soon."
    • changedInput schema / properties / type / enum
      Previous value: -[
      -  "company"
      -]New value: +[
      +  "company",
      +  "ticker"
      +]
    • changedInput schema / properties / value / description
      Previous value: -"Ticker (e.g., \"AAPL\") or zero-padded CIK (e.g., \"0000320193\"). Names not supported — use resolve_entity first if you only have a name."New value: +"Ticker (e.g., \"AAPL\"), zero-padded CIK (e.g., \"0000320193\"), or company name (e.g., \"Moderna\") — names resolve via SEC EDGAR company-name match."
  2. Added

TDQS

A4.4/5.0
Behavior5/5

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

Annotations already mark read-only/idempotent/non-destructive, and the description adds substantial non-obvious behavior: soft-fail for the USPTO sunset, expected empty fda_products for small-molecule-only companies, sources_used/sources_failed semantics, and resolved:false with notes for private companies. No contradiction with annotations.

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 information-dense, with trigger examples and the decisive 'ALWAYS PREFER' guidance front-loaded before the detailed source/output enumeration. Every clause carries a behavioral caveat or output field; slight redundancy around name resolution keeps it from the top score.

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 lacking an output schema, the description enumerates all major return sections (cik, recent_filings, fundamentals, patents, federal_contracts, fda_products, hiring, news, LEI, sources_used/sources_failed) and explains sorting/fallback semantics. It also covers invalid/private-company behavior and accepted input forms, so an agent has enough to invoke and interpret results.

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

Parameters3/5

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

The input schema already fully documents both parameters with examples and an enum, so the description need not add much; it paraphrases the same ticker/CIK/name resolution and notes interchangeability, adding only minor color. At 100% schema coverage, the baseline 3 applies.

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 concrete trigger phrases and states the core function: 'full cross-source profile of a US public company in ONE parallel call.' It enumerates the exact sources and a detailed output shape, and contrasts itself with 'chaining single-pack SEC/XBRL/news lookups,' so an agent can tell it apart from narrower research tools.

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 prefer this tool over chaining single-pack SEC/XBRL/news lookups when the user asks for a 'holistic view,' and provides natural-language examples that should trigger it. It does not enumerate exclusions against siblings like compare_entities or deep_research, so guidance is strong but not fully comprehensive.

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

The StackExchange tools are distinct, but the dominating data-lookup cluster is highly ambiguous: ask_pipeworx, ask_pipeworx_beta (explicitly identical today), ask_pipeworx_grounded, deep_research, and validate_claim all route into the same underlying tool catalog. The polymorpharket tools also overlap heavily, making selection between bet_research, polymarket_edges, polymarket_arbitrage, and fill-risk checks genuinely hard.

Naming Consistency2/5

The names are all snake_case but otherwise follow no consistent pattern: bare verbs (remember, forget, subscribe), prefixed names (pipeworx_feedback, stack_get_user), composite domain names (ask_pipeworx, generate_llms_txt), and generic verbs (resolve_entity, validate_claim, search_within). The StackExchange subset itself is split between stack_get_user/stack_tags and search_questions/get_answers.

Tool Count2/5

36 tools is already in the 'too many' range for one server, and the mismatch with the server name is severe: only 5 of 36 tools relate to StackExchange. The rest form a broad Pipeworx/prediction-market data platform that would itself be oversized for a focused purpose.

Completeness2/5

For a StackExchange-focused server, the surface has core read operations but lacks question-detail-by-ID, comments, related questions, or any write/community actions, and the 31 unrelated tools do not fill that gap. For the broader apparent Pipeworx platform coverage is broad, but the set has no single coherent domain against which completeness can be meaningfully judged.