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obstacle-analysis

Skill2 starsChanged 6 months agoApache-2.0View on GitHub

Identify what blocks the user from pursuing their chosen direction, assess severity, propose mitigations with search-validated evidence, and get user acceptance. Use after direction-narrowing has identified a specific direction.

The file

We split this skill into the rules it gives an agent

1 rule. About 0 are common, 0 are distinctive, and 1 is very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈0

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    After 2 rounds of ask-obstacle-acceptance with unresolved obstacles: return to present-candidates (direction-narrowing tactic)

    line 35

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Obstacle Analysis

Identify barriers, assess severity, propose mitigations, get acceptance.

Available SOPs

SOPPurposeExecution
identify-obstaclesIdentify obstacles from ActorProfile + chosen directionsubagent (search optional)
assess-obstacle-severityRate severity of each obstaclesubagent (search optional)
propose-mitigationsPropose evidence-backed mitigationssubagent (search required)
ask-obstacle-acceptancePresent obstacles + mitigations, get user decisiondialogue (search optional)

Search Tools Available (for all SOPs)

  • web-search (web-browsing): Quick web scanning, snippets
  • web-research (web-browsing): Full page reading + analysis
  • literature-overview (literature-engine): Paper landscape scan
  • literature-search (literature-engine): Medium-depth paper search (AI summaries)
  • literature-research (literature-engine): Deep paper reading (raw full text + PDF queries)

Methodology Guidance

  • SOPs can iterate within this tactic (re-assess after new information)
  • You decide whether additional search is needed to evaluate obstacles

Hard Constraint

  • Maximum 2 rounds of the full identify → assess → propose → ask cycle
  • After 2 rounds of ask-obstacle-acceptance with unresolved obstacles: return to present-candidates (direction-narrowing tactic)

Output (Tactic-Level Aggregation)

ObstacleReport { obstacles[], mitigations[], accepted: bool }

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