Neue Skills, Referenzen & OpenWiki-Doku integriert

Umfangreiche Erweiterung der Skill-Bibliothek: Neue Skills für Humanisierung (Englisch/PT-BR), Design-Validierung, AI-SEO und Coolify-Deployment inkl. Regelwerke, Presets, Pattern-Referenzen, Testfälle und Automatisierungsskripte. Zusätzliche Skills für Revenue-Centric Design, Pier Cloud, OKF, Lebenslauf- und LinkedIn-Optimierung sowie zahlreiche Referenzdateien, Checklisten und YAML/JSON/Markdown-Templates. Einführung einer vollständigen OpenWiki-Dokumentation mit Architektur-, Domain- und Workflow-Beschreibungen, zentralem Index und automatisierten Updates. Modularer Aufbau, restriktive Lizenzen und umfassende Qualitäts- und Evaluationsmechanismen für alle neuen Inhalte.
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Tim Krampitz
2026-07-26 14:00:58 +02:00
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# Control Rubric
Use this when setting gates, iteration caps, budgets, and stop conditions.
## Required Guards
- `loop_control.max_iterations`
- `gates.*.max_revisions`
- `loop_control.no_progress.max_stalled_iterations`
- At least one wall-clock, token, or USD budget cap when external models run.
The generated Python runner enforces wall-clock caps directly; token and USD
caps are advisory unless the chosen model CLI exposes accounting that the
loop operator wires in separately.
- A stop condition that describes success.
- A stop condition that describes no-progress or repeated failure.
## Good Gate Design
- Plan gate runs before delivery work.
- Delivery gate runs after each delivery artifact.
- Programmatic checks run before judge calls when possible.
- Human checkpoints sit at high-leverage points, usually after plan approval or
before external egress.
- Resume happens at gate boundaries unless the user explicitly needs finer
granularity.
## Execution Boundary
- Name where the loop is allowed to modify files: current workspace, branch,
worktree, throwaway directory, or an external orchestrator workspace.
- Identify actions with side effects: pushes, PR comments, Slack messages,
deploys, file deletes, database writes, or vendor sends.
- Decide whether side-effecting actions require approval, idempotency notes, or
duplicate-action checks.
- If the loop may run on a schedule or in parallel, call out the need for an
external orchestrator with concurrency controls.
## Failure Behavior
- Stop immediately when a hard cap is reached.
- Write the latest state to `loop-workspace/state.json`.
- Append each meaningful step, decision, check result, and blocker to
`loop-workspace/run-log.md`.
- Preserve review notes even when the gate fails.
- Stop or ask the human when the same blocker repeats for the configured
no-progress window.
- Do not let the host keep revising forever.
## Anti-Patterns
- No maximum iteration count.
- A judge gate with no judge.
- A budget cap in prose but not in `loop_control`.
- No no-progress detector.
- A loop that can send duplicate external notifications or repeat destructive
actions after restart.
- Scheduled or multi-agent work with no durable orchestrator or concurrency
story.
- Human signoff required but no checkpoint.
- Stop conditions that require subjective self-satisfaction.

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# Council Rubric
Use this when selecting reviewers and judges.
## Roles
`reviewer`
: Gives notes only. It may improve quality, but it cannot declare a gate clean.
`judge`
: Gives a structured verdict. It can be used as a gate `verdict_source`.
## Selection Guidance
- Prefer a different model family from the host for blind-spot coverage.
- Prefer local models such as `ollama` when privacy matters more than judgment
quality.
- Prefer a judge for gates that must block progress.
- Prefer a reviewer for brainstorming, adversarial notes, or tone critique
where a deterministic pass/fail would be fake precision.
- Keep council scope small: `plan`, `delivery`, or specific paths.
## Gate Rule
`verdict_policy: revise_until_clean` requires `verdict_source` to be either a
judge member or `human`. A reviewer-only gate can use `fixed_passes`, but it
cannot honestly claim clean.
## Judge Rubric Tips
- Name the artifact being judged.
- Name the exact criteria IDs.
- Ask for blocking issues, not general commentary.
- Require the fenced JSON verdict first or last.
- Keep the judge prompt short enough that the artifact, not the instruction
wrapper, dominates the context.
## Privacy Notes
Cross-vendor review can send project context to another CLI and vendor account.
Always name the destination, scope what it receives, apply redaction globs, and
require consent before the first send.

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# Goal Rubric
Use this when shaping the user's loop goal.
## Good Goal Shape
- Names the concrete outcome, not only the activity.
- Defines the artifact or state that proves the loop finished.
- Sets scope boundaries: included work, excluded work, and maximum depth.
- Names context sources the host must gather instead of assumptions it may make.
- Identifies the user, customer, system, or reviewer who will consume the result.
## Critique Prompts
- What would count as done if two competent agents disagreed?
- Which terms are subjective and need a measurable proxy?
- What context must be read before the host drafts a plan?
- What is explicitly out of scope for this loop?
- Can the goal be split into plan, delivery, and verification artifacts?
## Anti-Patterns
- "Improve the project" without a target artifact.
- "Make it good" without criteria.
- "Research X" without the decision the research supports.
- Goals where success depends on information the loop never gathers.
- Goals that require endless polishing with no stop condition.
## Better Examples
Weak: "Make our onboarding better."
Better: "Produce a 5-step onboarding workflow map for new enterprise users,
with each step assigned to a product surface, email, human owner, or missing
capability, and with no unresolved TBDs."
Weak: "Fix the flaky tests."
Better: "Identify and patch the root cause of the checkout test flake, prove it
with 20 local repeats or a CI rerun, and leave a short note explaining the
failure mode and the verification evidence."

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# Model Detection and Privacy Notes
Loop-architect detection is intentionally dumb and transparent. It stores
invocation metadata only, never credentials.
## Registry
Default registry path:
```text
~/.loop-architect/models.json
```
Registry entries should look like:
```json
{
"kiro": {
"cli": "kiro-cli",
"invoke": ["kiro-cli", "chat", "--trust-all-tools", "-p"],
"probe": ["kiro-cli", "--version"],
"available": true,
"authed": true,
"local": false,
"capabilities": {
"headless": true,
"goal": true,
"subagent": true,
"review_loop": true
}
},
"claude": {
"cli": "claude",
"invoke": ["claude", "-p"],
"probe": ["claude", "--version"],
"available": true,
"authed": true,
"local": false,
"capabilities": {
"headless": true,
"goal": true,
"subagent": false,
"review_loop": false
}
}
}
```
## Capabilities
`headless`
: The CLI accepts a prompt via stdin/argument and returns output via stdout
without interactive prompts. Required for use as host or judge in the
external Python runner.
`goal`
: The CLI supports a `/goal` command that runs an autonomous loop with
self-verification. When present, RUN_IN_SESSION.md can emit a `/goal`
one-liner as an alternative execution path.
`subagent`
: The CLI can spawn isolated sub-agents with their own context. When present,
the council can use native subagent review loops instead of shelling out.
`review_loop`
: The CLI supports iterative review loops with trigger-based feedback (e.g.
Kiro's `loop_to` with `NEEDS_CHANGES` trigger). Enables native cross-model
review without the external runner.
## Kiro CLI Specifics
- Headless mode requires `--trust-all-tools` or the session halts waiting for
tool approval.
- Full invoke pattern: `["kiro-cli", "chat", "--trust-all-tools", "-p"]`
- The `/goal --max N` command provides native loop execution with configurable
iteration limits (default 5).
- Subagent review loops use a `trigger` string (e.g. `NEEDS_CHANGES`) and
`max_iterations` cap.
## `authed` Semantics
`authed` means the basic probe command exited cleanly. It is a convenience
signal, not a guarantee that a future paid model call will succeed.
## Default Redactions
- `.env`
- `.env.*`
- `secrets/**`
- `**/*.key`
Add project-specific globs for customer data, private transcripts, or internal
design docs before sending anything to a non-local council member.
## Local Model UX
Surface `ollama` as the privacy-preserving option when present. It may be lower
quality than frontier hosted models, but it keeps council review in-house.

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# Verification Rubric
Use this when converting the user's definition of done into typed criteria.
## Taxonomy
`programmatic`
: A command or deterministic check returns pass/fail. Use this whenever
possible. Examples: tests, build, lint, schema validation, snapshot comparison,
or an extraction script that checks required headings.
`judge`
: A model scores a rubric and returns a structured verdict. Use this for
semantic quality that cannot be cheaply checked by code. The rubric must be
specific enough that a different model can apply it consistently.
`human`
: A person must sign off. Use this for taste, business judgment, private
knowledge, legal risk, or decisions where the user is the true authority.
## Required Fields
- Every criterion needs `id` and `type`.
- `programmatic` needs `check` as an argv array and `expect`.
- `judge` needs `rubric`.
- `human` needs `prompt`.
## Strong Criteria
- Check one thing at a time.
- Say what failure means.
- Prefer deterministic checks before model judgment.
- Make judge rubrics observable against artifacts the judge receives.
- Avoid relying on the host model to grade its own work.
## Anti-Patterns
- All criteria are judge or human criteria when tests or schema checks exist.
- "No errors thrown" as the only success criterion.
- Criteria that require hidden context not sent to the judge.
- Rubrics like "high quality" or "comprehensive" without dimensions.
- Programmatic checks written as shell strings instead of argv arrays.
## Structured Judge Contract
Judges should return a fenced JSON object:
```json
{
"verdict": "pass",
"blocking_issues": [],
"confidence": 0.86,
"notes": "The artifact satisfies the rubric."
}
```
Valid verdicts are `pass` and `revise`. If output cannot be parsed, the runner
will treat it as `revise` with a warning.