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Glama

Orcid

by io.github.pipeworx-io

Recent Changes

recent_changes
Read-onlyIdempotent

"What's new with X" / "latest on Y" / "what happened to Z this week / month / quarter" / "updates on Acme" / "news on Tesla recently" / "what's happening with Apple" — change feed for a company in the last N days/weeks/months in ONE parallel call. Fans out to SEC EDGAR (filings since since), GDELT→GNews fallback (news mentions in window — GDELT preferred, GNews when rate-limited or 5xx), USPTO (patents granted; PatentsView API sunset May 2025 so this soft-fails until reactivated). since accepts ISO date ("2026-04-01") or relative shorthand ("7d", "30d", "3m", "1y"). Returns structured changes[] grouped by source + total_changes count + pipeworx:// citation URIs. Use entity_profile instead when you want the static profile (filings + fundamentals + LEI + patents) regardless of window.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYesEntity type. Only "company" supported today.
sinceYesWindow start — ISO date ("2026-04-01") or relative ("7d", "30d", "3m", "1y"). Use "30d" or "1m" for typical monitoring.
valueYesTicker (e.g., "AAPL") or zero-padded CIK (e.g., "0000320193").

Schema Changelog

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

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Despite annotations already declaring readOnly/idempotent/non-destructive, the description adds substantial operational detail: parallel fan-out to SEC EDGAR, GDELT→GNews fallback on rate limits/5xx, USPTO soft-fail due to PatentsView API sunset, and the structure of returned changes[] with citation URIs. 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?

Well-structured with front-loaded examples and dense information, but the `since` format explanation duplicates the schema's parameter description, adding minor redundancy in an otherwise efficient description.

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 covers sources, fallbacks, return summary, time-window semantics, and the relevant alternative. The only missing details are individual change object fields, but the grouped changes[] description is sufficient for agent invocation.

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?

Schema description coverage is 100%, and all three parameters are clearly documented in the schema. The description repeats `since` formats and value semantics without adding new parameter-level information, so 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?

Description clearly identifies a 'change feed for a company in the last N days/weeks/months' with multiple source types, and explicitly distinguishes from sibling entity_profile by contrasting dynamic change feed vs static profile.

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?

Opens with natural-language query examples that signal intent, and explicitly instructs 'Use entity_profile instead when you want the static profile...' It also explains source fallback behavior, making when-to-use conditions clear.

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

C2.9/5.0
Disambiguation2/5

The ORCID-specific tools (record, search, works, work) are reasonably distinct, but the set is dominated by unrelated Pipeworx/Polymarket tools, several of which overlap heavily (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, discover_tools, suggest_questions). ask_pipeworx_beta is explicitly described as currently identical to ask_pipeworx, creating genuine misselection risk.

Naming Consistency2/5

Naming conventions are mixed with no consistent pattern: nouns like 'record', 'work', 'works', and 'education' sit alongside snake_case verb phrases like 'search_within', 'validate_claim', and 'generate_llms_txt', plus proprietary 'ask_pipeworx' / 'pipeworx_feedback' names. While readable, the styles are inconsistent enough that an agent cannot predict tool names from the domain.

Tool Count2/5

37 tools is far too many for a server scoped as 'Orcid': only roughly 7 tools (record, works, work, education, employment, search, search_within) actually relate to ORCID. The remaining ~30 tools cover prediction markets, npm dependencies, AI visibility, and generic Pipeworx/Polymarket functionality, which is a severe scope mismatch.

Completeness3/5

For read-only ORCID access, the surface covers full records, works, education, employment, and registry search, with semantic search over fetched records as a useful addition. However, it lacks other common ORCID activity types (funding, peer review, distinctions), profile metadata beyond summaries, and any create/update/delete lifecycle operations, leaving notable gaps for a server claiming to serve ORCID data.

Resources