Agenda Intelligence MD

Agenda Intelligence MD is a deterministic evidence-packet linter for claim-backed AI output.

Give it claims, the source IDs each claim relies on, optional quotations, and the supplied source text. It returns broken references, quote mismatches, lexical-support gaps, unmatched numbers, and the next reviewer actions.

It reports packet completeness, not whether a claim is true:

• not a factuality verifier;
• no autonomous live source retrieval;
• no authorization, approval, or compliance decision;
• human review is required for every result.

First run

Run the canonical synthetic packet from a source checkout:

git clone https://github.com/vassiliylakhonin/agenda-intelligence-md
cd agenda-intelligence-md
python -m venv .venv
.venv/bin/python -m pip install -e .
.venv/bin/agenda-intelligence check examples/evidence-packet/request.json

Expected shape:

packet_status=packet_complete claims=2 sources=1 factuality=not_assessed
  c1: packet_complete (lexical_support=supported, coverage=1.0)
  c2: packet_complete (lexical_support=supported, coverage=1.0)

Use JSON for an agent loop or CI pipeline:

.venv/bin/agenda-intelligence check examples/evidence-packet/request.json --format json
.venv/bin/agenda-intelligence check examples/evidence-packet/request.json --strict

--strict exits non-zero unless every claim is packet_complete.

Install the pinned release without cloning the source and check your own packet:

pip install "agenda-intelligence-md==1.4.0"
agenda-intelligence check /path/to/evidence-packet.json --strict

The evidence-packet contract

The request has two required collections:

• claims: a claim ID, claim text, declared source_ids, and optional verbatim quotes;
• sources: a source ID and the text supplied by the caller.

Request schema: schemas/v1/evidence-packet-request.schema.json

Response schema: schemas/v1/evidence-packet-response.schema.json

Runnable example: examples/evidence-packet/request.json

The response has three packet statuses:

factuality_status is always not_assessed. A complete packet can still rely on a wrong, stale, biased, or irrelevant source.

Python API

import json
from pathlib import Path

from agenda_intelligence.services import check_evidence_packet

packet = json.loads(Path("examples/evidence-packet/request.json").read_text())
result = check_evidence_packet(packet)
print(result["response"]["packet_status"])

The service layer is stateless. It does not persist packet contents or fetch missing sources.

What this is

• A small JSON contract for claim-backed AI output.
• A deterministic preflight before human review.
• A CLI and Python service suitable for local and CI use.
• An inspectable base for domain-specific compatibility profiles.

What this is not

• A general LLM evaluation platform.
• A GRC, vendor-management, or document-storage system.
• An agent authorization or policy-enforcement layer.
• Legal, compliance, sanctions, financial, investment, insurance, or trading advice.
• Proof that a source or claim is factually correct.

Why a repo full of markdown?

The repository predates the evidence-packet focus and also packages agent reasoning instructions. Files under skills/ are executable instructions for compatible agent runtimes, not ordinary prose documentation. They remain available for compatibility, but they are not the primary product interface.

MCP

The packaged MCP server exposes the same evidence-packet preflight to agent clients:

{
  "mcpServers": {
    "agenda-intelligence": {
      "command": "uvx",
      "args": ["--from", "agenda-intelligence-md", "agenda-intelligence-mcp"]
    }
  }
}

Run a focused stdio example against an editable install:

.venv/bin/python examples/evidence-packet/mcp_client.py \
  --command ".venv/bin/agenda-intelligence-mcp"

The example initializes the MCP server, calls check_evidence_packet with the synthetic packet, and prints only the review summary. See examples/evidence-packet/mcp_client.py and MCP.md.

Before using the result for an irreversible or high-stakes action, record the goal, supplied evidence, suspected unreliable evidence, assumptions, intended action, and stop/escalation conditions. The tool checks packet structure, not whether a claim is true or an action is authorized.

Existing MCP tools such as audit_claims, verify_quotes, grounded_check, and verify_claims remain compatible; no tool was removed or renamed.

Two authoring tools, create_brief and append_evidence, let an agent assemble a brief or an evidence pack step by step inside the contract instead of hand-building JSON and validating it afterwards. Both are deterministic and stateless: they validate on every call and return the document to the caller. They do not write files, retrieve sources, draft prose, or assess factual truth, and append_evidence never infers a supported claim status on its own.

Claude Code plugin installation also remains available:

/plugin marketplace add vassiliylakhonin/agenda-intelligence-md
/plugin install agenda-intelligence@agenda-intelligence

Compatibility profiles and adapters

The strategic-intelligence shell, HTTP API, A2A adapter, Cloudflare Workers, and five domain profiles remain in the repository. They demonstrate how the same service layer can be wrapped for different transports and domains. They are not the default commercial wedge and do not establish product-market fit.

The compatibility profiles are evidence-routing examples only. They do not provide legal, compliance, sanctions, financial, investment, insurance, or trading advice. Human review is required before any commercial action.

Verification Contract

The repository keeps three checks separate:

1. check reports packet completeness and lexical-support diagnostics.
2. grounded-check performs the older claim-to-corpus lexical diagnostic.
3. verify-claims applies declared freshness, authority, independence, jurisdiction, and identifier rules to caller-supplied evidence.

None discovers the right sources for the caller. verified in the bounded Claim Verdict contract means the supplied evidence meets that declared contract; it is not absolute truth.

Schemas

Canonical schemas live under schemas/v1/. Packaged copies under src/agenda_intelligence/data/schemas/v1/ must remain byte-equivalent; CI checks this invariant.

Start with:

• evidence-packet-request.schema.json
• evidence-packet-response.schema.json
• evidence-audit.schema.json
• claim-verification-request.schema.json

The full registry is in agent-manifest.json.

Before / after and benchmarks

The older agenda-analysis evaluation surface remains available for regression and compatibility work:

• examples/before-after/eu-ai-act.md
• examples/before-after/red-sea-shipping.md
• examples/before-after/sanctions-routing.md
• examples/source-backed/eu-ai-act.md

These are evaluation fixtures, not customer evidence or production benchmarks.

AnalysisBank

analysis-bank/ contains compatibility fixtures for reasoning-memory retrieval and failure-pattern regression. It is not part of the primary evidence-packet workflow.

Status

Current classification: portfolio-proof / build-to-learn.

Documentation

Repository layout

schemas/v1/                    public JSON contracts
src/agenda_intelligence/       Python service and transport adapters
examples/evidence-packet/      canonical packet example
tests/                         contract and regression tests
skills/                        compatibility agent instructions
deploy/cloudflare-worker/      compatibility Worker implementation
docs/                          reference and compatibility documentation

Development

pip install -e ".[dev]"
make ci
make verification-report

make verify-local also runs the compatibility Cloudflare Worker tests. make verification-report runs both verification surfaces and writes .verification/results.json: a deterministic, machine-readable record of the checks and hashed contracts. It uses no paid APIs and deliberately makes no claim about factual truth, live deployment health, adoption, or market value.

Roadmap

The next decision is adoption, not another vertical worker: test the evidence-packet contract on redacted practitioner artifacts, measure repeat use, and keep it portfolio-only if no repeated workflow appears. See ROADMAP.md.

License

MIT