Kjell Tore Guttormsen
6f861a0078
The expert reviewer was only a hardcoded verdict_input dict inside the offline simulation. Build it as the real, shared artifact target picture §8 calls for: shared/skills/expert-reviewer/ — a SKILL.md persona prompt (energy-advisor / M&V role + the realization-gap methodology the validator cannot compute) plus a canonical references/example-verdict.json. shared/ stays pure data; the MAF side reads it via portfolio_optimiser.persona.load_persona_example (call-time, fail-fast) and the Claude-SDK sibling reads the same JSON with its own loader. This de-stubs the simulation: its persona judgement (decision + rationale + traced marker) is now sourced from the artifact at call time, not an inline literal — so the shared persona is genuinely consumed and cannot rot silently. decision is binary (approved/rejected, the FeedbackContract the run path accepts); approved_with_adjustment is rejected there and lives only in the bundle seed frontmatter + the promotion gate, so the realization correction is carried in the rationale prose. Load-bearing trio (tests/test_persona_skill_loadbearing.py), each proven RED on its own detach: structure + framework-neutrality, the example is valid pipeline input (incl. FeedbackContract, on a throwaway copy), and the simulation's marker follows the artifact file. Suite 149->152. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01MHR8iKxJRxDiDfNw8HZmWE
39 lines
2.2 KiB
Markdown
39 lines
2.2 KiB
Markdown
# shared/ — framework-neutral core
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This directory holds the parts of the project that are **independent of any AI agent
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framework** and are meant to be **shared, unchanged, between both reference
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implementations**:
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- **this repository** — the method built on Microsoft Agent Framework (MAF);
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- **a sibling repository** (built later, in sequence) — the same method on the
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**Claude Agents SDK**.
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Sharing one identical core is what makes the two implementations a *fair comparison*:
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both consume the same concept, the same example data, and the same expected outcomes,
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so the only thing that differs is the agent framework itself.
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## Contents (growing)
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- [`CONCEPT.md`](CONCEPT.md) — the business concept, written for a non-specialist
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(e.g. a business developer at another company).
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- [`examples/bygg-energi-mikro/`](examples/bygg-energi-mikro/) — the first example knowledge
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bundle (OKF / LLM-wiki): one office building, one LED-retrofit measure, with a seed expert
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verdict encoding the realization gap and a golden-suite of expected validator outcomes. A
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small **dev fixture** for exercising the agentic loop; a realistic full-scale example comes later.
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- [`skills/expert-reviewer/`](skills/expert-reviewer/) — the **expert-reviewer persona** as a
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framework-neutral Agent Skill: a `SKILL.md` persona prompt (energy-advisor / M&V role + the
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realization-gap methodology the validator cannot compute) and a canonical
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`references/example-verdict.json`. Both reference implementations instantiate the reviewer from
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this one artifact; `shared/` stays pure data (each stack reads the JSON with its own loader).
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- *(planned)* the method specification.
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## Rules
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- **Nothing in here may import or depend on a specific agent framework.** If it does,
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it does not belong in `shared/`.
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- **Repo layout (decision R1, 2026-06-26):** the shared core lives here for now. When
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work on the sibling repository begins, it will be extracted into its own repository
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(e.g. `portfolio-optimiser-commons`) via `git subtree split`, and both implementation
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repos will consume it. This defers cross-repo plumbing until it is actually needed.
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See the target picture for the full architecture: `docs/plan/2026-06-26-maalbilde-agentic-loop.md`.
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