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Glama

Orcid

by io.github.pipeworx-io

Recent Alerts

recent_alerts
Read-onlyIdempotent

Pull fired events from your subscription feed. Returns the most recent alerts the evaluator has written to your persisted feed — each carries source, citation_uri (pipeworx:// when available), and the raw event payload. Filter by type (e.g. "sec_8k") and/or since (ISO timestamp). Set mark_read:true to flag returned events read so the next call only shows newer ones. Polls work fine; the same feed is also at GET registry.pipeworx.io/alerts.json for scripts and dashboards.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNoOptional — filter to one subscription type.
limitNoMax events to return (1-200, default 50).
sinceNoOptional ISO timestamp — return events fired_at >= this time.
mark_readNoFlag the returned events read in the same call (default false).
unread_onlyNoReturn only events where read_at is null (default false).

Schema Changelog

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

  1. Added

TDQS

A3.8/5.0
Behavior1/5

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

The description explicitly describes a mutating operation via 'Set mark_read:true to flag returned events read so the next call only shows newer ones', which contradicts the annotations readOnlyHint:true and idempotentHint:true. This is a significant annotation contradiction, and per rubric the score must be 1.

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

Conciseness5/5

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

The description is three sentences, front-loaded with the core verb and resource, and every sentence adds essential information: return contents, filtering/mark_read behavior, and polling/alternate endpoint. There is no filler or redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description is thorough for a feed-retrieval tool: it covers return fields, filtering, stateful mark_read, and an alternative HTTP endpoint. With no output schema, it sufficiently describes the return payload. It could mention pagination or default limit behavior, but the limit parameter is already in the schema, so a 4 is appropriate.

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 description coverage is 100%, giving a baseline of 3. The description adds value beyond the schema by providing a concrete type example ('sec_8k'), clarifying the since format as ISO timestamp, and explaining the consequence of mark_read on subsequent calls—making the behavior more understandable.

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 'Pull fired events from your subscription feed', which is a specific verb+resource pair. It distinguishes itself from sibling tools like list_subscriptions and recent_changes by explicitly mentioning the evaluator-written alerts, persisted feed, and the return fields (source, citation_uri, raw payload).

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 statement 'Polls work fine' gives clear usage context, and pointing to the same feed at GET registry.pipeworx.io/alerts.json offers an alternative for scripts/dashboards. However, it does not explicitly name when to use this tool over sibling MCP tools, though the context is 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