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Glama

Septa

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. First observed

TDQS

A4.5/5.0
Behavior5/5

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

Even with readOnlyHint, openWorldHint, and idempotentHint already declared, the description adds substantial behavioral context: parallel fan-out across eight sources, the USPTO PatentsView soft-fail until reactivation, the GDELT→GNews fallback chain, expected-empty fda_products semantics for small-molecule-only companies, 'an empty section is a real no data, not a bug', and the resolved:false-with-notes shape for private companies. Nothing contradicts the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

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

Information-dense, with nearly every sentence adding behavior that schema and annotations do not carry, and the trigger examples are front-loaded. But it is one unbroken wall-of-text paragraph mixing example phrasings, output specs, and edge cases, with a stray '?' after 'patents', a redundant closing `type` note, and the source list appearing twice.

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 fan-out tool with no output schema, the description carries the full burden of explaining return values and does so thoroughly: cik/company_name with resolution metadata, recent_filings with URIs, fundamentals fields, patents, federal_contracts, fda_products, hiring, news, LEI, plus sources_used/sources_failed for interpreting gaps. All input forms and known failure/empty behaviors are covered; an agent can invoke it and interpret results correctly without further lookups.

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 baseline is 3; the description adds concrete examples for each accepted value form ('AAPL', '0000320193', 'Moderna'), the resolved_from/resolved_to behavior when value is a name, and the private-company outcome — all beyond schema text. The closing sentence on `type` is largely redundant with the schema enum, slightly diluting the bonus.

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 — 'full cross-source profile of a US public company in ONE parallel call' — and opens with seven concrete trigger phrasings ('Tell me about X', 'research Acme', 'brief me on Tesla') that leave no doubt when it applies. It also explicitly distinguishes itself from chained single-source lookups ('ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups'), separating it from siblings like resolve_entity, compare_entities, and deep_research.

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?

The 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view' sentence is an explicit routing rule naming the discouraged alternative, and the trigger examples give clear when-to-use signals. It also implies no pre-resolution step is needed ('names now resolve via SEC EDGAR's company-name match'). However, it never explicitly names siblings like compare_entities or resolve_entity, and the private-company boundary is framed as an output condition (resolved:false) rather than a routing instruction.

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

A4.1/5.0
Disambiguation4/5

Most tools have distinct purposes, but there is some overlap among the ask_pipeworx variants (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded) and among the Polymarket tools (polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, polymarket_fill_risk, polymarket_kalshi_spread). However, detailed descriptions help differentiate them.

Naming Consistency3/5

Tool names mix conventions: snake_case is predominant, but there is no consistent verb_noun pattern. Some tools have 'septa_' prefix, but the majority do not follow a predictable structure. Naming is inconsistent across the set, though subgroups have some consistency.

Tool Count3/5

With 36 tools, the count is high. The server name 'Septa' suggests a focused transit server, but the tool set covers transit, data access, and prediction markets, making it overly broad. The number is borderline appropriate for a general-purpose server but misaligned with the name.

Completeness4/5

The transit domain is well-covered with alerts, positions, schedules, and train views. The data access and prediction market tools also cover their domains comprehensively. Minor gaps exist (e.g., no dedicated weather tool), but overall the tool set provides a wide range of capabilities.

Resources