ct_results_summaryProject posted ClinicalTrials.gov results for one NCT ID, including registered endpoints, reported outcome measures, statistical analyses, and adverse-event group counts. Registry results are not an FDA conclusion, peer review, or investment recommendation.
| Name | Required | Description | Default |
|---|---|---|---|
| nct_id | Yes | ||
| max_outcomes | No | Reported outcomes returned (1-50, default 20). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover the read-only, non-destructive nature. The description adds context about the scope of data included and includes a caveat that registry results are not an FDA conclusion, peer review, or investment recommendation, which goes beyond what annotations convey.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with no unnecessary words. The phrasing 'Project posted' is slightly awkward, but the content is focused and front-loaded with the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and only two parameters, the description provides a solid overview of the returned data categories and a caveat. It lacks details about pagination or how max_outcomes affects results, but overall it is sufficiently complete for a read-only tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already describes max_outcomes, while nct_id has no description (50% coverage). The description's phrase 'for one NCT ID' indirectly clarifies nct_id's purpose but provides no format details or further constraint. This is adequate but not fully compensating for the missing schema description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the tool retrieves ClinicalTrials.gov results for one NCT ID and enumerates the content (registered endpoints, outcome measures, statistical analyses, adverse-event counts). This clearly distinguishes it from sibling tools like ct_search or ct_get_study by focusing on posted results for a single trial.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as ct_get_study or ct_search. The description implies usage for retrieving result summaries, but it lacks explicit exclusions, prerequisites, or references to sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.