op1-marketing-seo-experiment-stage1
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Stage1 SEO Experiment Runner (Shadow)
Objective
Run the Stage1 SEO pipeline in shadow mode and produce auditable artifacts under research/stage1_marketing_seo/.
Single-cycle run
From workspace root:
./scripts/run_marketing_seo_stage1.sh --mode shadow --force
Check:
research/stage1_marketing_seo/run.latest.jsonresearch/stage1_marketing_seo/experiments.queue.latest.jsonresearch/stage1_marketing_seo/scoreboard.latest.jsonresearch/stage1_marketing_seo/decision_log.latest.md
1/2/3 validation run
Use the bundled helper:
python3 {baseDir}/scripts/run_rounds_123.py
This executes:
- Round1 baseline
- Round2 controlled handoff perturbation
- Round3 baseline restore + rerun
Then it writes snapshot artifacts and validation checks to:
research/stage1_marketing_seo/rounds/<timestamp>/rounds_1_2_3.report.mdresearch/stage1_marketing_seo/rounds/<timestamp>/rounds_1_2_3.report.json
Expected checks:
R1 == R3for queue/content reproducibilityR2 != R1for input-sensitivity
Guardrails
- Keep mode as
shadowfor Stage1 capability validation. - Treat this as experiment generation/scoring/queueing only (not auto publish).
- If run status is
blocked_input_incomplete, stop and report missing requirements fromrun.latest.json.input_sync.completeness.
References
references/stage1-output-contract.mdreferences/analysis-checklist.md
<!-- tomevault:4.0:skill_md:2026-05-22 -->Source: Daihaolin201/OperatorOne — distributed by TomeVault.
- Fluxly category
- Security
- Author-declared agents
- No explicit declaration found; this is not inferred or tested compatibility
- Static check
- 88 / 100 · heuristic scan, not runtime safety proof
- Author / version / license
- @tomevault-io · no license declared
- Fluxly token estimate
- Lean
- Fluxly setup estimate
- Guided setup
- External API key
- No requirement detected
- Detected OS requirements
- Unspecified
- Runtime requirements
- Unspecified
- Detected file/system behavior
-
- Read-only
- Shell exec
- Detected network behavior
- Local-only
- Install commands
- None (reference only)
Profile is derived at build time from SKILL.md and install vectors. Subject to drift from author intent.
Heads up: 未限定 allowed-tools,默认拥有全部工具权限。
The current SKILL.md does not define a fixed output example. Run the Stage1 SEO pipeline in shadow mode and produce auditable artifacts under research/stage1marketingseo/.
From workspace root: Check: research/stage1marketingseo/run.latest.json
Use the bundled helper: This executes: Round1 baseline
Keep mode as shadow for Stage1 capability validation. Treat this as experiment generation/scoring/queueing only (not auto publish). If run status is blockedinputincomplete, stop and report missing requirements from run.latest.json.inputsync.completeness.
references/stage1-output-contract.md references/analysis-checklist.md Source: Daihaolin201/OperatorOne — distributed by TomeVault.
# Stage1 SEO Experiment Runner (Shadow)
## Objective
Run the Stage1 SEO pipeline in shadow mode and produce auditable artifacts under `research/stage1_marketing_seo/`.
## Single-cycle run
From workspace root:
```bash
./scripts/run_marketing_seo_stage1.sh --mode shadow --force
```
Check:
- `research/stage1_marketing_seo/run.latest.json`
- `research/stage1_marketing_seo/experiments.queue.latest.json`
- `research/stage1_marketing_seo/scoreboard.latest.json`
- `research/stage1_marketing_seo/decision_log.latest.md`
## 1/2/3 validation run
Use the bundled helper:
```bash
python3 {baseDir}/scripts/run_rounds_123.py
```
This executes:
1. Round1 baseline
2. Round2 controlled handoff perturbation
3. Round3 baseline restore + rerun
Then it writes snapshot artifacts and validation checks to:
- `research/stage1_marketing_seo/rounds/<timestamp>/rounds_1_2_3.report.md`
- `research/stage1_marketing_seo/rounds/<timestamp>/rounds_1_2_3.report.json`
Expected checks:
- `R1 == R3` for queue/content reproducibility
- `R2 != R1` for input-sensitivity
## Guardrails
- Keep mode as `shadow` for Stage1 capability validation.
- Treat this as experiment generation/scoring/queueing only (not auto publish).
- If run status is `blocked_input_incomplete`, stop and report missing requirements from `run.latest.json.input_sync.completeness`.
## References
- `references/stage1-output-contract.md`
- `references/analysis-checklist.md`
---
> Source: [Daihaolin201/OperatorOne](https://github.com/Daihaolin201/OperatorOne) — distributed by [TomeVault](https://tomevault.io).
<!-- tomevault:4.0:skill_md:2026-05-22 --> Author text anchors workflow facts; Fluxly only indexes current sections, terms, files, and commands.
sections -> Objective → Single-cycle run → 1/2/3 validation run → Guardrails → References
terms -> This executes: 1. · --- > Source: [Daihaolin201/OperatorOne](https://github.com/Daihaolin201/OperatorOne) — distributed by [TomeVault](https://tomevault.io).
files/cmd -> research/stage1marketingseo/ · research/stage1marketingseo/run.latest.json · research/stage1marketingseo/experiments.queue.latest.json · research/stage1marketingseo/scoreboard.latest.json · research/stage1marketingseo/decisionlog.latest.md · research/stage1marketingseo/rounds/<timestamp>/rounds123.report.md · research/stage1marketingseo/rounds/<timestamp>/rounds123.report.json · R1 == R3
body sha256 -> 0394b249ac2a
Decide Fit First
Design Intent
How To Use It
Boundaries And Review