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pubmed-search-mcp

by u9401066
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Python
Remote

build_research_chronicle

Create a versioned, evidence-backed research chronicle tracking how a topic evolves, with citations, branches, provenance, and audit reports.

Instructions

Build a persisted, versioned, evidence-backed Research Chronicle.

A chronicle is the durable record of how a research topic evolved, and the single entry point for research-evolution work (it replaces the older one-shot timeline tools). It is stored with a monotonic revision number, so re-running it later produces revision N+1 and you can diff revisions to see exactly what changed.

The primary axis is chronological; research branches are a secondary organizing dimension. Both come from the same stored snapshot, and preserve shared provenance in output="timeline" and output="tree". Agreement between projections is not independent evidence verification.

Every entry carries:

  • a one-sentence claim with inline citations

  • supporting / contradicting / updating evidence articles

  • a research branch (lineage) assignment

  • provenance and a confidence score

The typed provenance graph links Topic → Branch → Entry → EvidenceArticle and is validated against edge invariants. The audit reports evidence coverage, identifier coverage, branch coverage, graph integrity, and chronology gaps, so you always know how complete the picture is.

Args: topic: Research topic (drug, gene, disease, intervention). Required unless pmids or a stored chronicle_id is supplied. pmids: Comma-separated PMIDs, or "last" to chronicle the previous search results instead of running a new search. max_events: Maximum timeline events to consider (topic mode). Omit to inherit the continued revision's value, else 30. min_year: Earliest publication year to include (topic mode). max_year: Latest publication year to include (topic mode). chronicle_id: Continue an existing chronicle (creates revision N+1) instead of deriving the ID from the topic. Passing it alone re-runs the stored scope, so the resulting diff shows research movement rather than a changed window. output: "summary" (default compact Markdown with the chronological spine), "json", "chronicle_map", "timeline", "tree", "graph", "evidence", "milestones", "mermaid" (horizontal time spine with lineage branches), or "narrative". "json", "chronicle_map", "timeline", "tree", "graph", "evidence", and "milestones" return JSON; the rest return Markdown.

Returns: The requested rendering plus an artifact locator when durable artifact persistence is enabled and succeeds. The artifact contains the full snapshot, projections, evidence table, milestone analysis, and audit regardless of output. Artifact failure is reported but does not roll back the already saved Chronicle revision.

Examples: build_research_chronicle(topic="remimazolam") build_research_chronicle(pmids="last", topic="My Reading List") build_research_chronicle(topic="CAR-T therapy", output="mermaid") build_research_chronicle(chronicle_id="remimazolam-9f2b1c4d")

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pmidsNo
topicNo
outputNosummary
max_yearNo
min_yearNo
max_eventsNo
chronicle_idNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.7.2

TDQS

A5/5.0
Behavior5/5

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

Beyond the annotations (readOnlyHint=false, idempotentHint=false, destructiveHint=false), the description discloses key behavioral traits: it persists a revision-numbered chronicle, re-running creates revision N+1, artifact failure is reported without rolling back the saved chronicle, and agreement between projections is not independent evidence verification. This is rich, non-obvious behavioral context.

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?

Although long, the description is tightly organized and information-dense: a front-loaded definition, a concise conceptual model, then a structured Args block and Returns explanation. Every section adds decision-relevant detail for a complex 7-parameter tool, and no sentence merely restates the tool name or schema.

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?

For a complex tool with no required parameters, no output schema, and three invocation modes, the description is complete. It covers all parameter interdependencies, rendering formats, return behavior, artifact persistence, and failure semantics, leaving no critical gap an agent would need to guess about.

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

Parameters5/5

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

Schema description coverage is 0%, so the description carries the full burden, and it delivers. Every parameter is semantically explained: topic's mutual exclusivity with pmids/chronicle_id, the special 'last' value for pmids, max_events inheritance behavior, year bounds, chronicle_id continuation semantics, and detailed return-type differences for output values.

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 opens with a precise verb-plus-resource statement: 'Build a persisted, versioned, evidence-backed Research Chronicle.' It then distinguishes itself from older one-shot timeline tools and names its role as the single entry point for research-evolution work, making it easy for an agent to differentiate this from siblings like read_research_chronicle.

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

Usage Guidelines5/5

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

The description makes usage conditions explicit: it replaces older one-shot timeline tools, topic mode versus pmids mode versus continuing via chronicle_id are clearly explained, and parameter-specific guidance (e.g., 'pmids="last"', 'Passing it alone re-runs the stored scope') tells the agent exactly when each invocation style is appropriate.

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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