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Automation
Skill

/identify-obstacles

Enumerate obstacles that block a target goal/direction, with type, evidence, and blocking relation.

From plugin
de-anthropocentric-research-engine
499200 skills
Install
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill identify-obstacles --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/identify-obstacles

Context preview

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

Enumerate obstacles that block a target goal/direction, with type, evidence, and blocking relation.

SKILL.md

identify-obstacles.SKILL.md
name: identify-obstacles
description: "Enumerate obstacles that block a target goal/direction, with type, evidence, and blocking relation."

identify-obstacles

Purpose

Enumerate obstacles blocking a target goal or direction, with evidence and blocking relations.

Input contract

required: [target_goal, current_state, domain_context]
optional: [timeline, resource_inventory, prior_failures]
constraints: [each obstacle has type, evidence, and blocking relation]

Procedure

1. Compare target requirements with current capabilities and constraints. 2. Enumerate technical, evidential, resource, temporal, and dependency obstacles. 3. Link each obstacle to blocked outcomes and supporting evidence. 4. Return severity, uncertainty, and candidate removal questions.

If obstacles have comparable evidence, severity, and tractability fields, consider `score-object` as the next tactic.

Output contract

produces: [obstacle_register, blocking_relations, evidence_links, removal_questions]
delta_fields: [findings, uncertainties, open_questions]

Quality gates

  • Every listed obstacle has a blocking relation and evidence or an explicit uncertainty label.
  • Duplicate obstacles are merged only when mechanism and remedy coincide.
  • Obstacles are separated from symptoms and desired outcomes.

Parameterization

Caller supplies goal schema, obstacle taxonomy, evidence fields, severity scale, and merge policy.

Failure and counterexamples

Reject generic risks, unsupported blockers, or lists with no relation to the target goal.

Provenance map

  • concept: north-star-crystallization/identify-obstacles
  • concept: experiment-execution/obstacle-identification
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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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Python
Language
Apache-2.0
License
6h ago
Last commit
7mo ago
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Repo: yogsoth-ai/de-anthropocentric-research-engine