contextualize

Detect application-context mismatch after execution. Verifies applicability when correct output may not fit the actual context, producing contextualized execution. Type: (ApplicationDecontextualized, AI, CONTEXTUALIZE, Result) → ContextualizedExecution. Alias: Epharmoge(ἐφαρμογή).

Quality

17%

Does it follow best practices?

Impact

—

No eval scenarios have been run

Securityby

Passed

No known issues

Optimize this skill with Tessl

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

Quality

Discovery

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 extremely abstract and jargon-laden, reading more like an academic type theory notation than a practical skill description. It fails to communicate concrete actions, natural trigger terms, or explicit guidance on when Claude should select it. A user or Claude would have great difficulty understanding what this skill actually does or when to use it.

Suggestions

Replace abstract language with concrete actions: describe what specific task this skill performs in plain language (e.g., 'Checks whether generated output fits the user's actual context and adjusts it accordingly').

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 match the user's specific situation or context'.

Remove the type signature notation and Greek alias, which add no value for skill selection and obscure the description's purpose.

Dimension	Reasoning	Score
Specificity	The description uses highly abstract, jargon-heavy language like 'application-context mismatch', 'contextualized execution', and a type signature. No concrete actions a user would recognize are listed.	1 / 3
Completeness	The 'what' is buried in abstract language and the 'when' is entirely missing — there is no 'Use when...' clause or equivalent explicit trigger guidance. Both dimensions are very weak.	1 / 3
Trigger Term Quality	There are no natural keywords a user would say. Terms like 'ApplicationDecontextualized', 'Epharmoge(ἐφαρμογή)', and 'ContextualizedExecution' are opaque technical/academic jargon that no user would naturally use in a request.	1 / 3
Distinctiveness Conflict Risk	The description is so abstract and niche that it's unlikely to accidentally trigger for other skills, but it's also so vague that it's unclear what domain it belongs to, making it hard to positively distinguish from other abstract skills.	2 / 3
	Total	5 / 12 Passed

Implementation

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 reads more like an academic paper or type-theoretic proof than actionable guidance for Claude. While the underlying concept (detecting when correct results don't fit the application context) is valuable, the presentation buries practical guidance under layers of formal notation, redundant restatements, and abstract type definitions. The document would benefit enormously from separating the formal specification into a reference file and presenting a concise, example-driven overview in the SKILL.md body.

Suggestions

Extract the formal specification (FLOW, MORPHISM, TYPES, CONVERGENCE, MODE STATE blocks) into a separate REFERENCE.md file and keep SKILL.md as a concise actionable overview with 1-2 concrete examples of mismatch detection and surfacing.

Add at least one concrete end-to-end example showing: a specific result R, a specific context X, a detected mismatch, the surfacing format in practice, and the adaptation outcome — this would make the protocol dramatically more actionable.

Consolidate the 22 rules, UX safeguards table, and severity table into a compact checklist or move them to a separate RULES.md, keeping only the 3-5 most critical rules inline.

Remove redundant restatements — the workflow is described in FLOW, MORPHISM, PHASE TRANSITIONS, LOOP section, and then again in the Protocol section. One clear description with the surfacing template is sufficient.

Dimension	Reasoning	Score
Conciseness	Extremely verbose and dense with formal type theory notation, extensive rule lists, and abstract definitions that Claude already understands conceptually. The document is hundreds of lines long with redundant restatements of the same concepts in different formalisms (flow, morphism, types, phases, rules). Much of this could be condensed to a fraction of the size.	1 / 3
Actionability	The protocol does provide concrete phase sequences, surfacing format templates, and task creation formats that are somewhat actionable. However, much of the content is abstract formal specification rather than executable guidance — there are no real-world examples of input/output, no concrete code beyond pseudo-formal TaskCreate templates, and the heavy formalism obscures what Claude should actually do in practice.	2 / 3
Workflow Clarity	The multi-phase workflow (Phase 0 → Phase 1 → Phase 2 → loop) is clearly sequenced with explicit transitions and re-scan triggers, and validation checkpoints exist. However, the workflow is buried under layers of formal notation, redundant restatements across FLOW, MORPHISM, PHASE TRANSITIONS, LOOP, and Protocol sections, making it hard to follow. The re-scan feedback loop is well-defined but the sheer density undermines clarity.	2 / 3
Progressive Disclosure	The content is a monolithic wall of text with no bundle files or external references to offload detail. The formal type definitions, all 22 rules, UX safeguards, severity tables, and dimension taxonomy are all inlined in a single massive document. The formal specification block alone could be a separate reference file, with the SKILL.md serving as an actionable overview.	1 / 3
	Total	6 / 12 Passed

Validation

100%

Warnings & errors only

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

Validation — 11 / 11 Passed

Validation for skill structure

No warnings or errors.

Repository: jongwony/epistemic-protocols
Commit: a1acc87

Reviewed: 3 days ago

Table of Contents

Discovery Implementation Validation

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