aibvf-mcp

validate_portfolio

Read-onlyIdempotent

Check whether a supplied AI BVF v1.0 portfolio document has the shape the portfolio tools require, before scoring, sequencing, storing or sharing it. CALL THIS when the document came from a file, another system or hand-built JSON and its structure is uncertain. It checks required fields, taxonomy values and 0–100 pillar ranges only; it does not judge the evidence or calculate a verdict. Pillars may be bare numbers or { value, confidence } objects, both are valid. Use assemble_portfolio when the user has a list of initiatives in conversation and needs the document built for them, score_portfolio when the document is already ready for verdicts, and sequence_portfolio only after its initiatives are scoreable. Returns valid=true or one error per failing JSON path. Pure deterministic validation — no network, auth, or side effects.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`portfolio`	Yes	The portfolio document as a JSON object following the AI BVF v1.0 schema: a top-level object with bvf_version, organization, and a non-empty "initiatives" array, each initiative carrying the same fields score_initiative expects (industry, revenue_eur, function, ai_tier, readiness, and a scores object with the four 0–100 pillars, each either a bare number or an object { value, confidence? }; both shapes pass). Checked structurally only — required fields present, correct types, enum values valid, pillar numbers in range; the pillar values are NOT scored or judged here (use score_initiative or score_portfolio for that). On failure, errors[] names each failing JSON path and the rule it broke.

Output Schema

TableJSON Schema

Name	Required	Description
`valid`	Yes	True when the portfolio conforms to the schema.
`errors`	Yes	Empty when valid; otherwise one entry per schema violation.
`bvf_version`	Yes	AI BVF protocol version validated against.

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedJul 6, 2026

changedInput schema / properties / portfolio / description

Previous value: -"The portfolio document as a JSON object following the AI BVF v1.0 schema: a top-level object with bvf_version, organization, and a non-empty \"initiatives\" array, each initiative carrying the same fields score_initiative expects (industry, revenue_eur, function, ai_tier, readiness, and a scores object with the four 0–100 pillars). Checked structurally only — required fields present, correct types, enum values valid, pillar numbers in range; the pillar values are NOT scored or judged here (use score_initiative or score_portfolio for that). On failure, errors[] names each failing JSON path and the rule it broke."New value: +"The portfolio document as a JSON object following the AI BVF v1.0 schema: a top-level object with bvf_version, organization, and a non-empty \"initiatives\" array, each initiative carrying the same fields score_initiative expects (industry, revenue_eur, function, ai_tier, readiness, and a scores object with the four 0–100 pillars, each either a bare number or an object { value, confidence? }; both shapes pass). Checked structurally only — required fields present, correct types, enum values valid, pillar numbers in range; the pillar values are NOT scored or judged here (use score_initiative or score_portfolio for that). On failure, errors[] names each failing JSON path and the rule it broke."

First observedJul 5, 2026

TDQS

A4.9/5.0

Behavior5/5

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

Disclosure goes beyond annotations: states it is 'pure deterministic validation — no network, auth, or side effects', explains what it does not do ('does not judge the evidence or calculate a verdict'), and clarifies valid pillar shapes. 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.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Description is concise, well-structured, and front-loaded. Every sentence adds unique value without repetition or fluff. The first sentence immediately states purpose and context.

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 input schema details, output schema existence, and lack of output schema shown in input, the description covers validation behavior, return format (valid=true or errors), and scope. No gaps remain for the agent to select and invoke 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?

Schema coverage is 100%, but the description adds significant value: explains the portfolio document structure (bvf_version, organization, initiatives array), the validation scope (required fields, taxonomy, ranges), and the acceptable score shapes (bare number or object). This exceeds schema descriptions.

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 clearly states the tool validates an AI BVF v1.0 portfolio document with the verb 'check' and resource 'shape'. It explicitly distinguishes from siblings by naming assemble_portfolio, score_portfolio, and sequence_portfolio with their specific use cases.

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?

Provides explicit guidance: 'CALL THIS when the document came from a file, another system or hand-built JSON and its structure is uncertain.' Also specifies when to use alternatives (assemble_portfolio, score_portfolio, sequence_portfolio), giving clear when-not-to-use context.

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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