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context-engineering-advisor

Diagnose context stuffing vs. context engineering. Use when an AI workflow feels bloated, brittle, or hard to steer reliably.

57

Quality

67%

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tessl review fix ./skills/context-engineering-advisor/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

56%Weight 40%Scale 1-5

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

The body is a well-structured, actionable diagnostic workshop with strong sequencing, templates, and worked examples, but it is severely over-long: a large conceptual primer restates knowledge Claude already has and every core framework is repeated multiple times. Splitting primer/examples/pitfalls into reference files would materially improve both conciseness and progressive disclosure.

Suggestions

Move the "Key Concepts" primer (parametric/contextual intelligence, RAG, vector DBs, memory types) into a separate references file; SKILL.md should assume Claude's knowledge and keep only the diagnostic framework.

Eliminate the repetition of the 5 diagnostic questions and the Research→Plan→Reset→Implement cycle — present each framework once and reference it from the steps instead of restating it in Key Concepts, the relevant step, and Common Pitfalls.

Split the three worked examples and Common Pitfalls into an examples.md / pitfalls.md reference so SKILL.md becomes a lean overview with one-level-deep, clearly signaled references.

DimensionReasoningScore

Conciseness

The ~760-line body includes a large "Key Concepts" primer explaining parametric vs. contextual intelligence, RAG, vector databases, and declarative/procedural memory — concepts Claude already knows — and repeats each framework (5 diagnostic questions, Research→Plan→Reset→Implement, memory architecture) two to three times. It is above a 1 because genuine actionable diagnostic structure exists underneath the padding, but the verbosity and repetition are substantial.

2 / 5

Actionability

Concrete diagnostic questions, a select-all symptom list, a Context Manifest template, a Falsification Protocol with good/bad examples, three detailed worked examples, and specific heuristics (persist 80%+, retrieve <20%) give mostly executable guidance. It is below a 5 because many steps rely on placeholders like "[Agent customizes based on user's workflow]" and "[Agent provides] specific recommendations" that are not fully concrete.

4 / 5

Workflow Clarity

Step 0 through Step 9 form a clearly sequenced diagnostic flow with branching checkpoints (symptom-count thresholds 0-1/2-3/4+) and "Agent validates" gates. It is not a 5 because there is no strong validate→fix→retry feedback loop, and not a 3 because the sequence and decision points are explicit; the destructive/batch cap-3 rule does not apply to this advisory skill.

4 / 5

Progressive Disclosure

No bundle files exist and the SKILL.md is a 760-line monolith with the concept primer, all nine steps, three worked examples, and five pitfalls inlined — the under-50-line exception does not apply. It is above a 2 because sections are well-headed and the workshop-facilitation and related-skill references are clearly signaled, but below a 4 because content that clearly belongs in separate files (concepts, examples, pitfalls) is all inline.

3 / 5

Total

13

/

20

Passed

Description

78%Weight 40%Scale 1-5

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

The description cleanly follows the high-quality [what]. Use when [triggers] pattern, explicitly answering both what and when with natural symptom language. Its main weakness is specificity: it surfaces only the diagnostic framing and leaves the skill's concrete tactical practices unmentioned.

Suggestions

Add one or two concrete tactical actions to the description (e.g., "identify context boundaries" or "implement bounded domains and episodic retrieval") to lift specificity above a single 'diagnose' verb.

Include a couple of common trigger synonyms users might say (e.g., 'prompt', 'agent', 'hallucination', 'RAG') to broaden natural keyword coverage.

DimensionReasoningScore

Specificity

Quotes "Diagnose context stuffing vs. context engineering" name the domain plus one concrete action, but the description omits the skill's tactical practices (bounded domains, episodic retrieval, Research→Plan→Reset→Implement) listed in the body. It is above a 2 (it is not generic) but below a 4 (no list of several specific actions).

3 / 5

Completeness

"Diagnose context stuffing vs. context engineering" answers what, and "Use when an AI workflow feels bloated, brittle, or hard to steer reliably" answers when with concrete trigger phrases — matching the 5-anchor pattern exactly. It cannot be a 4 because both what and when are explicit and concrete.

5 / 5

Trigger Term Quality

"AI workflow feels bloated, brittle, or hard to steer reliably" are natural symptom phrases a user would actually say, giving good keyword coverage. It is below a 5 because common synonyms/variants (prompt, agent, hallucination, RAG, context window) are missing, and above a 3 because the triggers are concrete natural language rather than jargon.

4 / 5

Distinctiveness Conflict Risk

The context-engineering niche and its triggers are mostly distinct with minimal conflict risk. It is not a 5 because "AI workflow" and "improving AI output quality" overlap with general AI-advisor and prompt-engineering skills — an overlap the body itself acknowledges ("Not about writing better prompts").

4 / 5

Total

16

/

20

Passed

Validation

81%

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

Validation13 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

skill_md_line_count

SKILL.md is long (776 lines); consider splitting into references/ and linking

Warning

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

relative_links

Relative link issues: 5 suspicious

Warning

Total

13

/

16

Passed

Repository
deanpeters/Product-Manager-Skills
Reviewed

Table of Contents

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