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Clinicaltrials

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).

TDQS

A3.9/5.0
Behavior1/5

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

Description describes mutating behavior (mark_read:true flags events as read), but annotations declare readOnlyHint=true, creating a direct contradiction between tool's advertised read-only nature and actual state-changing capability.

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?

Three concise sentences, front-loaded with purpose. Every sentence adds useful information without redundancy.

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?

Covers return fields (source, citation_uri, payload), filtering, state change via mark_read, polling suitability, and alternative access for scripts. All key behaviors explained despite no output schema.

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 baseline is 3. Description adds value by explaining mark_read's effect on subsequent calls, providing example for type filter, and clarifying since accepts ISO timestamps.

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?

Clearly states 'Pull fired events from your subscription feed' with verb 'pull' and resource 'subscription feed alerts'. Distinct from sibling tools like list_subscriptions and recent_changes.

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?

Provides filtering guidance (type, since), explains mark_read for pagination, and notes polling is safe. Mentions alternative URL for scripts/dashboards, but does not explicitly compare to siblings or state when not to use.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Clinicaltrials toolsInspect
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TDQS

A3.9/5.0
Disambiguation3/5

Tool families overlap in purpose—ask_pipeworx/ask_pipeworx_beta/ask_pipeworx_grounded, ct_search/ct_count_by_condition/ct_competitive_landscape, and ct_sponsor_trials/ct_sponsor_pipeline/ct_sponsor_activity all present multiple plausible entry points. The very detailed, cross-referenced descriptions help, but an agent still has to read carefully to avoid misselection.

Naming Consistency4/5

Nearly all tool names follow lowercase snake_case with recognizable prefixes like ct_, polymarket_, and pipeworx_, giving the set a strong overall pattern. The main deviation is noun-phrase names such as recent_changes, entity_profile, and pipeworx_trending instead of a more uniform verb-first convention.

Tool Count2/5

44 tools is far too many for a server named Clinicaltrials: only 13 are ct_* tools, while the other 31 are broad Pipeworx utilities covering prediction markets, memory, subscriptions, npm scanning, and AI visibility. The clinical-trial module itself is well-sized, but the server bundles substantial unrelated surface area.

Completeness4/5

The clinical-trial workflow is nearly complete: search, study details, results, counts, sponsor comparison and pipeline, location lookup, update tracking, and landscape mapping are all covered. Minor conveniences like saved searches or export are missing, but agents can work around them; there are no dead ends in the registry domain.

Resources