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contextualize

Detect application-context mismatch after execution. Verifies applicability when correct output may not fit the actual context, registering each mismatch through a fail-closed deficit-fit certificate before adaptation, producing contextualized execution. The transformative revalidation loop is non-monotone — adapting the result mutates the evaluation target and can breed emergent mismatches; re-scan is mandatory. This is the non-monotone/transformative side of the contextualize ↔ distill boundary (distill is the monotone/read-only-of-source side). Type: (ApplicationDecontextualized, AI, CONTEXTUALIZE, Result) → ContextualizedExecution. Alias: Epharmoge(ἐφαρμογή).

27

Quality

17%

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Passed

No known issues

Optimize this skill with Tessl

npx tessl skill review --optimize ./epharmoge/skills/contextualize/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

27%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

This skill is an extremely dense formal specification that prioritizes mathematical rigor and completeness over practical usability. The same concepts are restated 5-10 times across different sections (flow, morphism, types, phase transitions, convergence, rules), creating massive redundancy. While the underlying workflow (detect mismatch → certify → surface → adapt → re-scan) is sound, it is nearly impossible to extract actionable guidance from the formal notation and repeated qualifications.

Suggestions

Reduce the document by 70-80% by stating each concept once: define types in one section, workflow in another, and rules in a third — eliminate the massive redundancy where certificate-before-registration, transformative revalidation, and fail-closed semantics are each restated in FLOW, MORPHISM, TYPES, PHASE TRANSITIONS, LOOP, CONVERGENCE, Protocol sections, and Rules

Extract the formal type definitions, convergence proofs, and composition rules into a separate REFERENCE.md or FORMAL.md file, keeping SKILL.md focused on the actionable workflow with clear steps

Add 1-2 concrete worked examples showing an actual mismatch detection on a real result (e.g., 'User asked for a Python script, result uses os.system() but project conventions use subprocess') with the exact surfacing output Claude should produce

Replace the dense formal notation in the main workflow sections with plain-language step descriptions, reserving formal notation for the reference file only

DimensionReasoningScore

Conciseness

Extremely verbose and repetitive. The same concepts (fail-closed certificate, transformative revalidation, non-monotone loop, certificate-before-registration) are restated dozens of times across sections. The formal specification alone is massive, and then the Protocol section re-explains everything again in prose. Much of this is internal formal machinery that Claude doesn't need spelled out repeatedly — the document could be 80%+ shorter while preserving all actionable content.

1 / 3

Actionability

The skill provides concrete surfacing formats, task creation templates, and structured option presentations that are somewhat actionable. However, the overwhelming majority of content is abstract formal specification (type definitions, convergence proofs, morphism declarations) rather than executable guidance. There are no concrete examples of actual mismatch detection on real results, and the formal notation dominates over practical instruction.

2 / 3

Workflow Clarity

The phase transitions (Phase 0 → Phase 1 → Phase 2 → loop) are clearly sequenced and validation checkpoints exist (certificate checks, re-scan after adaptation). However, the workflow is buried under layers of formal notation and repeated qualifications. The actual steps are hard to extract from the dense specification. The re-scan/validation loop is well-defined but the presentation makes it difficult to follow in practice.

2 / 3

Progressive Disclosure

The entire specification is a monolithic wall of text with no references to external files despite the enormous length and complexity. Content that could be split (formal type definitions, convergence proofs, composition rules, detailed phase transition specifications) is all inline. With no bundle files provided, the skill dumps everything into a single massive document with no layering or navigation structure beyond section headers.

1 / 3

Total

6

/

12

Passed

Description

7%

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

This description is nearly incomprehensible, relying on invented terminology, academic-sounding abstractions, and type signatures that provide no practical guidance. It fails to communicate what the skill actually does in concrete terms, includes no natural trigger terms a user would use, and lacks any explicit 'when to use' guidance. It would be essentially unusable for skill selection in a real system.

Suggestions

Rewrite the description using plain language that describes concrete actions (e.g., 'Checks whether generated output fits the user's actual context and adapts it if there is a mismatch').

Add an explicit 'Use when...' clause with natural trigger terms a user might say, such as 'Use when the output seems correct but doesn't fit the user's specific situation or application context'.

Remove invented jargon like 'deficit-fit certificate', 'epharmoge', and type signatures, replacing them with terms users and Claude can naturally match against.

DimensionReasoningScore

Specificity

The description uses highly abstract, jargon-heavy language ('fail-closed deficit-fit certificate', 'non-monotone/transformative side of the contextualize ↔ distill boundary') without listing any concrete, understandable actions a user would recognize.

1 / 3

Completeness

The 'what' is buried in impenetrable abstraction and the 'when' is missing entirely — there is no 'Use when...' clause or any explicit trigger guidance for when Claude should select this skill.

1 / 3

Trigger Term Quality

There are no natural keywords a user would ever say. Terms like 'epharmoge', 'non-monotone', 'deficit-fit certificate', and 'ApplicationDecontextualized' are invented jargon that no user would use in a request.

1 / 3

Distinctiveness Conflict Risk

Ironically, the extreme obscurity of the jargon means it is unlikely to conflict with other skills, since no normal query would match these terms. However, it is also unlikely to ever be correctly triggered, and the underlying purpose is so unclear it could overlap with anything involving 'context' or 'validation'.

2 / 3

Total

5

/

12

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation11 / 11 Passed

Validation for skill structure

No warnings or errors.

Repository
jongwony/epistemic-protocols
Reviewed

Table of Contents

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