Zetesis Scientific Due Diligence

Retrieve dated public evidence for a claim

zetesis_evidence

Read-only

Step 2 of a Zetesis evaluation. Runs the search queries against public evidence sources (Europe PMC, ClinicalTrials.gov, openFDA, and optionally NIH RePORTER and SEC EDGAR) and returns a deduplicated bundle where every source carries a hard public id, followed by the Zetesis grading rubric so you can grade the dimensions yourself.

With as_of set, retrieval is fenced to sources published, registered, or filed on or
before 31 December of that year, and two fields that leak later outcomes are
suppressed: a trial's present-day status, and FDA labels effective after the cutoff.
That makes it possible to judge a claim on what was actually knowable at the time.

Runs no model, costs nothing, and returns immediately. Takes the queries worked
out when the claim was scoped.

Args:
    queries: 3 to 6 short keyword phrases. Query 1 should be the bare name of the
        thing claimed about (a drug, compound code, model, or gene); query 2 that
        name plus at most two outcome words. Longer phrases retrieve commentary
        rather than the primary report.
        If the claim names no agent at all (a behaviour, diet, procedure, exposure
        or policy), anchor on the field's own technical term instead of the lay one
        ("time restricted eating", not "intermittent fasting"), pair it with the
        outcome as the field measures it, and allow one design word such as
        crossover or randomized in one later query. Without an entity name that
        design word is the only thing separating a trial report from a review of
        trial reports.
    as_of: optional cutoff year, as used in zetesis_scope.
    include_capital: also retrieve funding and public-filing signal.

Input Schema

TableJSON Schema

Name	Required	Description
`as_of`	No	Year the claim was made. Set it for any claim that is not brand new: it restricts evidence to what existed then, which keeps later outcomes out of the reading and sharply improves what is retrieved.
`queries`	Yes	Three to six short keyword phrases. Query 1 should be the bare name of the thing claimed about; query 2 that name plus at most two outcome words.
`include_capital`	No	Also retrieve funding and public filing signal from NIH RePORTER and SEC EDGAR.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed3 schema fields changedSep 5, 2026

addedInput schema / properties / as_of / description

Added value: +"Year the claim was made. Set it for any claim that is not brand new: it restricts evidence to what existed then, which keeps later outcomes out of the reading and sharply improves what is retrieved."

addedInput schema / properties / include_capital / description

Added value: +"Also retrieve funding and public filing signal from NIH RePORTER and SEC EDGAR."

addedInput schema / properties / queries / description

Added value: +"Three to six short keyword phrases. Query 1 should be the bare name of the thing claimed about; query 2 that name plus at most two outcome words."

First observedSep 1, 2026

TDQS

A4.3/5.0

Behavior5/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false; the description goes well beyond by revealing that it 'Runs no model, costs nothing, and returns immediately,' deduplicates results, and explains the as_of fencing that suppresses later-outcome fields. 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?

The description is front-loaded with the main purpose, then covers behavioral context suppressed fields and cost, and ends with an args section. It is long and dense, but every sentence carries substantive information, especially the query-building guidance.

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?

With an output schema present, the description need not restate returns; it covers sources, dedup behavior, ID assignment, grading rubric inclusion, temporal fencing, cost/speed, and parameter details. An agent has enough context to invoke the tool correctly.

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?

The schema already covers all parameters with descriptions, so the baseline is 3. The description adds substantial query-construction meaning: bare name first, outcome words second, technical vs lay terms, and design-word guidance. as_of is given the helpful pointer 'as used in zetesis_scope'.

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 clearly states a specific verb+resource: 'Runs the search queries against public evidence sources ... and returns a deduplicated bundle where every source carries a hard public id.' It positions itself as 'Step 2 of a Zetesis evaluation', but does not explicitly contrast itself with sibling tools like evaluate_claim or verify_attestation.

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 strong contextual guidance: it is Step 2, takes 'queries worked out when the claim was scoped,' and includes detailed instructions for constructing queries and setting as_of. However, it never explicitly says when not to use it or names alternatives such as zetesis_scope or evaluate_claim.

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

All Zetesis Scientific Due Diligence tools Inspect

Try in Browser

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.