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Glama

Linkedin Humblebrag

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

A4.5/5.0
Behavior5/5

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

Annotations already mark the tool read-only, open-world, idempotent, and non-destructive. The description goes well beyond that by disclosing the fan-out across sources, soft-failure behavior for USPTO PatentsView, the meaning of empty sections ('a real "no data", not a bug'), and the private-company resolved:false path with a notes line. This is exceptionally transparent about expected behavior and failure modes.

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 front-loaded with purpose and usage guidance, and the extensive output-key explanation is necessary because there is no output schema. The trigger examples are helpful, though somewhat repetitive, and the input format guidance reappears near the end. Overall it is dense and well-organized, but a bit verbose.

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 complex tool with no output schema, the description is remarkably complete: it lists return sections, explains resolved_from/resolved_to, covers soft-failures, distinguishes empty results from errors, describes the private-company case, and defines accepted input forms. An agent has enough context to invoke the tool correctly and interpret its results.

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

Parameters5/5

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

Even though the schema already documents both parameters at 100% coverage, the description adds valuable meaning: `type` accepts 'company' or 'ticker' interchangeably, `value` can be a ticker, zero-padded CIK, or company name, and names resolve via SEC EDGAR's company-name match. It also gives concrete examples like 'AAPL', '0000320193', and 'Moderna', which clarify the accepted shapes beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's job: build a 'full cross-source profile of a US public company in ONE parallel call,' supported by trigger examples like 'Tell me about X' and 'company profile for Microsoft.' It distinguishes itself from chained single-pack SEC/XBRL/news lookups, but it does not explicitly differentiate from sibling tools like compare_entities or deep_research, leaving some ambiguity for an agent choosing among them.

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 description gives strong, explicit guidance: 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view.' It also provides trigger phrases and explains how private companies and no-data cases behave. However, it does not state when to prefer alternatives or when this tool is inappropriate (e.g., single-fact lookups, comparisons), so the when-not-to-use guidance is incomplete.

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
Disambiguation3/5

Most tools are distinctly named and the descriptions are unusually specific, but the set contains overlapping families: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all route to the same underlying data, and the beta variant is currently an exact duplicate. The entity/company lookup, AI-visibility, and Polymarket clusters also require reading the long descriptions to choose correctly.

Naming Consistency3/5

All names are lowercase snake_case and readable, with useful prefixes like ask_pipeworx, polymarket_, and pipeworx_. However the macro pattern is mixed: many are verb-first (compare_entities, resolve_entity), many are noun phrases (entity_profile, polymarket_edge_tracker, recent_alerts), and one puts the verb last (linkedin_humblebrag_generate).

Tool Count2/5

32 tools is far too many for a server whose apparent name and stated LinkedIn-humblebrag purpose are served by exactly one tool. Even viewed as a general Pipeworx/research utility, the surface is bloated: duplicate ask variants, multiple meta-tools, and a sprawling prediction-market family push the count well past the 25-tool threshold.

Completeness2/5

For the domain implied by the server name, the surface is severely incomplete: only generation exists, with no way to list, edit, delete, publish, or manage LinkedIn-humblebrag posts. The de facto Pipeworx research domain is much better covered, but the overall set has serious dead ends because the one LinkedIn tool is isolated and the core tools are oriented toward a different, unrelated workflow.

Resources