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Skill

/formated-specs

Spec-slot skill for the research-executor. Emit the 4-layer DARE orchestration of the assigned topic as one research-graph JSON fenced block in your reply. Replaces the generic spec-writing step.

From plugin
de-anthropocentric-research-engine
393200 skills
Install
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill formated-specs --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/formated-specs

Context preview

The summary Claude sees to decide when to auto-load this skill.

Spec-slot skill for the research-executor. Emit the 4-layer DARE orchestration of the assigned topic as one research-graph JSON fenced block in your reply. Replaces the generic spec-writing step.

SKILL.md

formated-specs.SKILL.md
name: formated-specs
description: Spec-slot skill for the research-executor. Emit the 4-layer DARE orchestration of the assigned topic as one research-graph JSON fenced block in your reply. Replaces the generic spec-writing step.

formated-specs

You occupy the spec step of the research executor. Instead of writing a spec file, you emit the orchestration you are about to (notionally) run as a single JSON object inside one fenced block, directly in your reply.

Hard contract

1. Emit exactly one fenced block opened with ` ```research-graph ` (that exact info-string, hyphen, NOT ` ```json `) and closed with ` ``` `. 2. The block body is a single valid JSON object, the schema below. 3. Emit it **into your reply (the dialogue)** — do NOT write it to a file. The block lands in this session's transcript; the harness cuts it from there. 4. Atomicity: produce the whole block within one assistant turn. 5. If you revise after pushback, emit a new full `research-graph` block; the harness keeps the LAST one. Never emit a half block. 6. Mandatory final step: after the graph block, load and run `formated-results`.

research-graph schema

{
  "nodes":        [ {"id": "n1", "skill": "<skill-name>", "layer": "campaign|strategy|tactic|sop"} ],
  "edges":        [ {"from": "n1", "to": "n2", "kind": "calls|sequences"} ],
  "layer_labels": { "n1": "campaign|strategy|tactic|sop" },
  "manifest":     [ "<skill actually orchestrated>" ],
  "prereq_dag":   [ {"node": "n2", "requires": ["n1"]} ]
}

Populate `manifest` only with skills you actually orchestrated; do not fabricate. `layer` and `layer_labels` must respect the 4-layer architecture (campaign → strategy → tactic → sop). Judge nothing against academic standards; this is a structural record of orchestration only.

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Ships withde-anthropocentric-research-engine

The complete research orchestration system for AI-native science. What It Does Design Philosophy Architecture (v3.2.2) Quick Start Configuration Roadmap License DARE is not a tool that helps you do research. It is the researcher.

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Repo: yogsoth-ai/de-anthropocentric-research-engine