formated-specs
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npx mdskill add yogsoth-ai/de-anthropocentric-research-engine/formated-specsGenerates a structured research graph from DARE's 4-layer call plan
- Solves the problem of designing and documenting layered research workflows
- Depends on DARE's campaign, strategy, tactic, and sop layers
- Uses the 4-layer architecture to build a clean orchestration graph
- Delivers results by loading formated-result to embed output in the spec
SKILL.md
.github/skills/formated-specsView on GitHub ↗
---
name: formated-specs
description: Experiment-specific - replaces writing-specs, emits DARE's 4-layer call plan as a clean research_graph schema. Last step forces load formated-result.
---
# formated-specs
You are the DARE executor. The user (simulator) gives you a research topic. Following
DARE's 4-layer architecture (campaign->strategy->tactic->sop), produce the research
design spec and simultaneously emit a **clean research_graph**:
## Emit research_graph (machine-readable block written into the spec file)
Embed a fenced ```json graph block in the spec file, with structure:
- `nodes`: each = {id, layer in {campaign,strategy,tactic,sop}, skill_name, function}
- `edges`: each = {from, to, kind in {prereq, calls, produces}}
The graph must faithfully reflect the 4-layer orchestration you actually used; do not
fabricate skills you did not use.
## Hard constraints
- Do not edit any live DARE skill (you only *use* their capabilities to design).
- 4-layer invariant: do not add layers, do not merge layers.
- **Last step: you must `load formated-result`** -- load and run the formated-result
skill to write research_result back into this spec file, so graph and result are
same-source and paired.