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Glama

Github_private

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.

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

A4.8/5.0
Behavior5/5

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

Annotations already indicate a safe read-only, idempotent operation, and the description goes well beyond that by disclosing fan-out sources, per-section return behavior, soft-fail semantics for USPTO patents, expected empty results for fda_products, and the meaning of sources_used/sources_failed. It also explains resolved:false handling for non-public companies.

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 the tool is complex and there is no output schema, so the description must carry return-format detail. It is front-loaded with trigger examples and the core directive, then organized by output section. Some density could be split, but every sentence earns its place.

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 of this scope with no output schema, the description is remarkably complete: it enumerates all return sections, source coverage, failure modes, input variants, and expected empty results. An agent has enough context to call it correctly and interpret results without additional documentation.

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%, so the schema already documents type and value. The description adds value with concrete examples, clarifies that 'company' and 'ticker' behave identically, and explains name resolution via SEC EDGAR and zero-padded CIK formatting. This enriches rather than merely restates the schema.

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 states a specific verb and resource: producing a full cross-source profile of a US public company. It is clearly differentiated from sibling tools by framing itself as the holistic single-entity lookup and even names the alternative pattern (chaining single-pack lookups) that it replaces.

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 gives explicit trigger phrases, instructs 'ALWAYS PREFER' this tool for holistic company views, and specifies acceptable input forms (ticker, CIK, or name) plus expected behavior for private companies. It clearly tells the agent when this tool is the right choice and when not to expect success.

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

There is significant overlap among many tools: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, and validate_claim all serve query-answer purposes with subtle differences, and multiple polymarket tools (polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, polymarket_fill_risk, polymarket_kalshi_spread) cover similar arbitrage/mispricing territory. Additionally, ai_visibility_check and scan_competitor_ai_presence clearly overlap, making it hard to pick the right one.

Naming Consistency2/5

Tool names follow no consistent pattern. Some use a gh_ prefix (gh_get_file, gh_get_repo, etc.), others are descriptive phrases (ask_pipeworx, compare_entities, bet_research), and a few are plain verbs (remember, recall, forget, subscribe, unsubscribe). The mixed conventions and varied verb/noun styles make the set feel disjointed.

Tool Count3/5

At 37 tools, the count is high but still within a usable range. However, the server is named 'Github_private' yet includes only 7 GitHub-specific tools and 30+ unrelated tools (Pipeworx data, Polymarket betting, memory, etc.). This suggests the server aggregates multiple unrelated domains, making the count feel bloated for its apparent GitHub purpose.

Completeness2/5

Given the server name, the GitHub tool surface is severely incomplete: there are no create/update/delete operations for repos, no PR creation or merging, no issue comments, no branches, and no search across repos. The Pipeworx side is fairly comprehensive, but the mismatch between the server name and the actual tool set leaves major gaps for expected GitHub workflows.

Resources