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yogsoth-aiyogsoth-ai/de-anthropocentric-research-engine/skills/assess-readiness-dimension/SKILL.md

assess-readiness-dimension

Skill505 starsChanged 50 days agoApache-2.0View on GitHub

Assess one readiness dimension against explicit anchors/evidence.

1 other project uses a version of this.

Adopted by

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The file

We split this skill into the rules it gives an agent

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

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈1

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

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

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Do not average incomparable readiness dimensions.

    line 29

≈ “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

assess-readiness-dimension

Purpose

Assess one readiness dimension against explicit anchors, evidence, and known deficits.

Input contract

required: [subject_record, readiness_dimension, anchor_definition, evidence_register]
optional: [scoring_scale, prior_assessment]
constraints: [anchor levels are ordered and observable; every score cites evidence and a deficit statement]

Procedure

  1. Define the dimension, scale, anchor descriptions, and decision relevance.
  2. Map each supplied evidence item to the strongest supported anchor and record contrary evidence.
  3. Assign the lowest defensible level whose requirements are met; record missing requirements separately.
  4. Emit the dimension score, evidence basis, deficits, and reassessment trigger.

Output contract

produces: [readiness_level, evidence_basis, deficit_list, reassessment_trigger]
delta_fields: [findings, evidence_updates, uncertainties, decisions, open_questions]

Quality gates

  • A-class gate: declared universe = all requirements of the readiness dimension; numerator = requirements supported by at least two independent evidence items; batch increment = one requirement assessed; stopping reason = all requirements assessed or a blocking deficit is established; source references = evidence and anchor IDs; direction/threshold reason = level rises only when its anchor requirements are met and falls when blocking contrary evidence dominates.
  • A level without a deficit or uncertainty statement is invalid.

Failure and counterexamples

Do not average incomparable readiness dimensions. A high score on one dimension cannot erase an unmet hard requirement on another.

Provenance map

  • resolved: dimension-assessment

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