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Ct Enrollment Watch

ct_enrollment_watch
Read-onlyIdempotent

Route active trials for enrollment follow-up using registry status, enrollment type, dates, last update, and site counts. Flags are mechanical review hints—not predictions of recruitment success, trial failure, or data timing.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
phaseNo
queryNo
sponsorNoOptional company name. Matched against the registered LEAD sponsor by default.
sponsor_matchNoWhich sponsor role the name must fill. "lead" (the default) returns only trials whose registered LEAD sponsor is that company. "lead_or_collaborator" also returns trials led by someone else that list the company as a collaborator — typically academic trials of the company's drug. Every returned study carries sponsor_match_field naming which one matched.

TDQS

A3.5/5.0
Behavior4/5

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

The annotations already cover safety traits (read-only, idempotent, non-destructive). The description adds valuable behavioral context by clarifying that flags are mechanical review hints and not predictions of recruitment success, trial failure, or data timing. This goes beyond the annotations and helps prevent misinterpretation.

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 two sentences with no filler. The core action and criteria are front-loaded, and the interpretative caveat is separated into its own sentence. Every word earns its place.

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

Completeness3/5

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

For a read-only tool with no required parameters, the description gives enough to understand the purpose and avoid misreading flags. However, with no output schema, the agent still lacks a clear picture of what a 'routed' result looks like and how to express the enrollment/status/date criteria in a query.

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

Parameters2/5

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

With schema coverage at only 40%, the description needed to explain the actual parameters, but it does not clarify limit, phase, query, or how to specify the enrollment/status/date criteria it mentions. The description adds little operational detail beyond the schema's existing definitions.

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 states a specific action ('route') and resource ('active trials for enrollment follow-up'), with clear criteria such as registry status, enrollment type, dates, last update, and site counts. It is clear about the tool's function, though it does not explicitly distinguish it from sibling clinical-trial tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The phrase 'for enrollment follow-up' implies a use case, and the caveat that flags are mechanical hints provides some guidance on how to interpret output. However, there is no explicit statement about when to prefer this tool over alternatives like ct_search or ct_sponsor_activity.

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

A3.6/5.0
Disambiguation1/5

Several tools appear to do the same thing at the top level: ask_pipeworx, ask_pipeworx_beta (explicitly identical today), and ask_pipeworx_grounded are near-duplicate routing entry points, and deep_research overlaps heavily with them. Among the ct_* tools, ct_count_by_condition, ct_competitive_landscape, ct_sponsor_pipeline, and ct_compare_sponsors all provide overlapping counting/landscape functionality, making correct selection genuinely ambiguous.

Naming Consistency4/5

The overwhelming majority of tools use lowercase snake_case and mostly follow a verb_noun or domain-prefixed pattern (ct_search, ct_get_study, list_subscriptions, validate_claim, resolove_entity). Some names are noun phrases rather than verbs (ct_competitive_landscape, entity_profile, polymarket_edge_tracker) but the overall style is consistent and readable, with only minor deviations.

Tool Count2/5

44 tools is far too many for a server named 'Clinicaltrials'; only 13 tools are actually clinical-trials-specific while the rest span general data lookup, prediction markets, memory, subscriptions, and npm scanning. The count is inflated by redundant entry points (ask_pipeworx/beta/grounded) and overlapping ct tools, making the set feel heavy and unfocused.

Completeness4/5

For the clinical-trials registry domain, the surface is largely complete: search, full study details, results summaries, condition counts, sponsor pipelines, location-based lookup, recent updates, and catalyst tracking are all represented. Minor gaps exist (e.g., historical versions/protocol amendments and advanced filter combinations), but most could be worked around via the universal ask_pipeworx router.