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musharna

data-aggregator-mcp

by musharna

resolve

Read-only

Retrieve full research dataset metadata and files by ID, with optional citation formatting, FAIR scoring, retraction status, and license advisory. Export formats include Croissant and RO-Crate.

Instructions

Fetch the full DataResource for a known id (e.g. 'zenodo:7654321', 'datacite:10.5061/dryad.x', 'hf:owner/name', a bare Zenodo record id, or a DOI), including the complete files[] manifest. Publication resolve also attaches normalized identifiers (pmid/pmcid/doi) and, when open access, a full-text file. Pass cite= to render a citation onto the result (citation field); omitted means no citation. Pass trust=true to attach retraction status (via Crossref) under trust{}. Pass fair=true to attach an RDA-grounded FAIRness score (0–100 + F/A/I/R sub-scores + actionable gaps) computed from the record under fair{}. Pass use= (commercial/redistribute/modify/ml-training) to attach a licence-compatibility advisory (ALLOW/REVIEW/DENY, not legal advice) under license_compat{}. Pass format=provenance for a one-call RO-Crate 1.1 data-availability dossier (under provenance{}) composing version-currency, licence+SPDX, FAIR score, retraction status, and the source/DOI/ID chain — it auto-attaches fair + trust.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesSource-prefixed id, bare Zenodo id, or DOI
useNoWhen set, attach a licence-compatibility advisory under license_compat{} for an intended use of the record. Supported intents: 'commercial', 'redistribute', 'modify', 'ml-training' (training = a derivative+commercial use, our stated interpretation). The verdict is ALLOW/REVIEW/DENY computed from a bundled choosealicense.com licence matrix keyed on the normalized SPDX id, naming the governing clause — a metadata-derived advisory, NOT legal advice. An unrecognized or absent licence yields REVIEW (never a fabricated ALLOW/DENY); an unknown intent is an error.
citeNoOptional citation format to render onto the result: 'bibtex', 'ris', 'csl-json', or any CSL style name ('apa', 'mla', 'vancouver', ...). DOI-bearing records render via DOI content negotiation; non-DOI records support 'csl-json' only. Omitted = no citation. Failures degrade quietly (citation stays null).
fairNoWhen true, attach an RDA-grounded FAIRness assessment under fair{}: a 0–100 overall score plus findable/accessible/interoperable/reusable sub-scores, the count of indicators evaluated, and actionable gaps each naming its RDA FAIR Data Maturity Model indicator id. Pure/local — no network call. Only the machine-evaluable subset is scored (never fabricates what the metadata cannot show).
trustNoWhen true, attach trust signals (retraction status via Crossref) to the result under trust{}. One extra Crossref call; only meaningful for DOI-bearing records (a DataCite data DOI Crossref does not register leaves retracted=null = unknown, never a false clean claim).
formatNoOptional export to render onto the result. 'croissant' attaches a file-level Croissant JSON-LD manifest (croissant field); 'ro-crate' attaches a minimal RO-Crate 1.1 manifest (ro_crate field); 'provenance' attaches a one-call RO-Crate 1.1 data-availability dossier (provenance field) bundling version-currency, licence+SPDX, FAIR score, retraction status, and the source/DOI/ID chain — it auto-attaches fair{} and trust{} so the dossier is complete in one call (unknown signals are reported as unknown, never as a clean claim).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYes
doiNo
fairNo
kindYes
taxaNo
yearNo
filesNo
linksNo
titleYes
trustNo
accessNo
sourceYes
fundingNo
licenseNo
metricsNo
mirrorsNo
citationNo
creatorsNo
organismNo
ro_crateNo
subjectsNo
croissantNo
is_latestNo
accessionsNo
provenanceNo
descriptionNo
identifiersNo
access_modesNo
last_updatedNo
superseded_byNo
license_compatNo
Behavior5/5

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

Beyond the readOnlyHint=true annotation, the description details behaviors of all optional parameters (e.g., 'fair is pure/local, no network call', 'trust only for DOI-bearing records', 'failures degrade quietly') and explains auto-attachment in provenance mode, offering comprehensive transparency.

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 core purpose and efficiently lists parameters with concise explanations. Though lengthy, it packs necessary detail without redundancy. Slightly more brevity could improve score.

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

Completeness4/5

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

Given the tool's complexity (6 parameters, optional nested outputs) and the presence of an output schema, the description covers all intended behaviors and edge cases. It does not explicitly describe the base return structure, but output schema likely fills that gap.

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?

Schema description coverage is 100%, providing baseline 3. The description adds extra context for each parameter (e.g., 'use' explains verdict logic and matrix, 'cite' lists supported formats and fallbacks), elevating clarity beyond the schema alone.

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 'Fetch the full DataResource for a known id', providing a specific verb and resource, and includes example IDs, which clearly defines the tool's purpose and distinguishes it from siblings like search (query-based) and fetch (likely simpler).

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 intended usage (resolve by known ID) is implicit from the purpose, but the description does not explicitly contrast with siblings or state when not to use it. No exclusions or alternative tool mentions are provided.

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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