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Generic, open framework on Microsoft Agent Framework (MAF): multi-agent cost-saving proposals gated by a mandatory deterministic validator, with HITL learning.
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Kjell Tore Guttormsen 2613a5183e docs(research): MAF 1.9.0 capability map — feature-utilization for Fase 2 [skip-docs] 
Two independent grounded passes (installed-source introspection + official MS
Learn via MCP) produce a per-need adopt/keep decision table for using MAF
features well in Fase 2, instead of reinventing them.

Headline: Microsoft's Workflows "State Isolation" page documents verbatim the
exact footgun Spike B(b) found today — a reused Workflow accumulates agent
threads across runs; the fix is a fresh-instance-per-run factory. Our
fresh_workflow() IS the official pattern.

Key verdicts: ADOPT real UsageDetails token counts + a budget ChatMiddleware +
native builder round caps + GA @tool/MCP + observability; KEEP the hand-rolled
structural VerdictStore and inline validator (MAF memory/eval are the wrong
shape); ROLL a tiny role->deployment map (declarative is preview/not installed).
Corrections recorded: CLAUDE.md "Magentic experimental" stands at doc-level (no
code gate); Spike D extend_instructions is two-arg (source_id, instructions).

Skills answer: method-as-Skill yes (MAF consumes SKILL.md natively, experimental);
MAF-docs-mirror Skill no (rots vs live MCP); the digest lives in this map.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Fif1r1En5W542HbZV88yMH
2026-06-24 11:36:26 +02:00
.claude/projects/2026-06-23-fase1-derisk-spikes docs(fase1): trekreview round-2 ALLOW — Fase 1 formally closed [skip-docs] 2026-06-24 11:15:41 +02:00
docs docs(research): MAF 1.9.0 capability map — feature-utilization for Fase 2 [skip-docs] 2026-06-24 11:36:26 +02:00
spikes fix(fase1): spike B fan-out measures real conversation bleed, not a counter 2026-06-24 11:09:55 +02:00
src/portfolio_optimiser feat(fase0): synthetic reference domain (D4) + backend profile skeleton (D2) 2026-06-23 22:38:41 +02:00
tests fix(fase1): spike B fan-out measures real conversation bleed, not a counter 2026-06-24 11:09:55 +02:00
.gitignore feat: initial scaffold (Python framework on Microsoft Agent Framework) 2026-06-23 22:01:22 +02:00
.python-version feat: initial scaffold (Python framework on Microsoft Agent Framework) 2026-06-23 22:01:22 +02:00
CHANGELOG.md feat: initial scaffold (Python framework on Microsoft Agent Framework) 2026-06-23 22:01:22 +02:00
CLAUDE.md build(fase1): add dev orchestration + solver + async deps, scaffold spikes 2026-06-24 09:57:57 +02:00
pyproject.toml build(fase1): add dev orchestration + solver + async deps, scaffold spikes 2026-06-24 09:57:57 +02:00
README.md feat: initial scaffold (Python framework on Microsoft Agent Framework) 2026-06-23 22:01:22 +02:00
uv.lock build(fase1): add dev orchestration + solver + async deps, scaffold spikes 2026-06-24 09:57:57 +02:00

README.md

portfolio-optimiser

Generic, open framework on Microsoft Agent Framework (MAF) for finding cost-savings / efficiency proposals within each project of a portfolio of independent projects. Multiple agents collaborate to generate candidate proposals; a mandatory deterministic validator (solver + Monte Carlo) decides the numbers; domain experts review via human-in-the-loop, and the system learns from their verdicts.

Status: Early development (plan phase). Not yet usable.

Disclaimer — technical framework only. This project is a technical framework. Organizations that deploy it are themselves responsible for ensuring a valid processing purpose and for any required assessments (DPIA, risk/ROS, security reviews, etc.). The framework ships technical affordances (local-only mode, provenance/audit logging, no silent data egress) to enable compliant use, but makes no compliance guarantees.

Design philosophy

The result will never fit any single customer 100%. The goal is a ~90% genuinely generic core plus clear extension points, so competent people can configure the last mile per customer. We deliberately do not chase the final 10%.

Docs

Stack

Python ≥3.10 · MAF (agent-framework) · uv. Backend profiles: Azure/Foundry (full) + local (fallback).

Develop

uv sync
uv run pytest
uv run ruff check .