phasefolio

query_landscape

Read-onlyIdempotent

Fetch the asset-anchored competitive landscape for a project — comparable trials, competing programs, sponsor activity, and biomarker overlap. Sourced from CT.gov + FDA + PhaseFolio's curated enrichment. Use when an analysis question asks 'who else is working on this?' or 'what's the competitive context?'

Input Schema

TableJSON Schema

Name	Required	Description
`project_id`	Yes	UUID of the project to anchor the landscape on. Indication × modality × biomarker filters derive from the project.
`phase_filter`	Yes	Optional list of clinical phases to include (e.g. ['PHASE2','PHASE3']). Empty array means all phases.
`recency_years`	Yes	How many years back to look (1–50). Defaults to 10 — broad enough to catch development-stage peers without polluting with stale failures.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`data`	Yes	Asset-anchored landscape payload: kpis (sponsor counts, trial counts, etc.), comparable_trials[] (NCT-keyed), competing_programs[], biomarker_overlap. Filtered by the project's indication × modality × biomarker.

TDQS

A4.3/5.0

Behavior4/5

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

Annotations already provide readOnlyHint and idempotentHint. The description adds value by disclosing data sources (CT.gov, FDA, PhaseFolio) and the nature of the output (curated enrichment, asset-anchored), which goes beyond the annotations. No contradiction.

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?

Two sentences: first defines scope and content, second gives usage guidance. No redundant or filler language; every word earns its place.

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?

Given the presence of output schema, full parameter descriptions, and rich annotations, the description covers purpose, usage, sources, and content. There are no material gaps for an agent to select and invoke the tool correctly.

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

Parameters3/5

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

Schema coverage is 100%, so baseline is 3. The description does not add parameter-specific syntax or constraints; it only alludes to project-derived filters, which the schema already states. No additional value beyond schema.

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 uses a specific verb ('Fetch') and resource ('asset-anchored competitive landscape'), enumerating concrete components (comparable trials, competing programs, sponsor activity, biomarker overlap). This clearly distinguishes it from siblings like get_dossier or get_evidence.

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?

Explicitly says when to use it via example questions ('who else is working on this?' / 'what's the competitive context?'). It does not name alternatives or explicitly state when not to use, but the context is clear and actionable.

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

A4.4/5.0

Disambiguation5/5

Each tool targets a distinct entity or operation: get_* fetches specific objects, query_* searches datasets, list_scenarios enumerates, while triage_asset and verify_export are standalone actions. There is no functional overlap or ambiguity among the 13 tools.

Naming Consistency5/5

All tools follow a consistent verb_noun pattern in lowercase with underscores. The verbs (get, list, query, triage, verify) clearly indicate the action, and nouns identify the target. This uniform scheme makes the tool purpose predictable.

Tool Count5/5

With 13 tools, the server is well-scoped within the ideal 3–15 range. Each tool addresses a specific aspect of the drug-development analysis domain (project/scenario context, evidence, methodology, benchmarks, risk, landscape, SEC deals, dossier, verification, triage) without redundancy.

Completeness4/5

The read-side surface is thorough for the domain: projects, scenarios, evidence, methodology, benchmarks, drug risk, landscape, SEC deals, dossier, export verification, and triage are all covered. The only minor gap is the lack of a list_projects tool, but get_project can fetch a known project, providing a workaround.

Resources

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