CtrlK
BlogDocsLog inGet started
Tessl Logo
SkillPublic

agentic-engineering

Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing. Use when planning or executing engineering work that agents will carry out end to end.

Quality

76%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide
SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

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

Quality

Content

75%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 content is efficient, actionable, and well-structured: concrete code, a model-tier routing map, a feedback-loop eval process, and a checklist-style classification table. It consistently sits just below excellent because of small trimmable redundancies, missing templates for the vaguer directives, and a long inline deep-dive section that could be split into a reference file.

DimensionReasoningScore

Conciseness

Sections are lean and directive (e.g. 'Haiku: classification, boilerplate transforms, narrow edits'; the 15-minute unit rule), assuming Claude's competence. Minor trimmable instances remain: 'Redact secrets and private document data before logging or sharing' states a generic norm Claude already knows, and the closing paragraph on writes/retries is redundantly worded. Efficient with minor over-explanation, not fully lean.

4 / 5

Actionability

Provides an executable JavaScript adapter (with its illustrative nature explicitly justified: 'Replace this adapter with the actual tool's contract'), a concrete model-tier mapping, specific tracked cost fields, and an expected-classification table. Mostly executable guidance with minor gaps — no template or example for defining completion criteria, capability evals, or failure signatures.

4 / 5

Workflow Clarity

The Eval-First Loop is a clear baseline → execute → re-run → compare feedback loop, and the tool-result section gives an ordered three-boundary check with a recovery policy for writes and batch failures. Minor validation gaps: no explicit recovery step when eval deltas regress, and the overall flow across sections (decomposition → routing → sessions → evals) is presented as parallel lists rather than one sequenced workflow.

4 / 5

Progressive Disclosure

The body is well-organized with clear section headers, no buried references, and no bundle files to navigate (none exist). The ~75-line tool-result interpretation procedure with code and table is deep-dive content that could arguably live in a separate reference file, keeping SKILL.md as a leaner overview — a minor organization gap that keeps it below the top anchor.

4 / 5

Total

16

/

20

Passed

Description

67%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 is specific and well-structured, with an explicit 'Use when...' clause and distinctive methodology terms in third-person voice. Its main weakness is trigger-term coverage: the phrasing is abstract and misses the natural synonyms users would actually say when needing this skill.

Suggestions

Add concrete natural trigger phrases to the 'when' clause, e.g. 'Use when the user asks to delegate implementation to agents, run an AI coding workflow end to end, or set up evals for agent-built features.'

Include common user-side synonyms such as 'delegate', 'agent workflow', 'evals', or 'model selection' so the description matches how users naturally phrase these requests.

DimensionReasoningScore

Specificity

Names three specific practices — 'eval-first execution, decomposition, and cost-aware model routing' — in third person, matching the anchor for several specific actions with minor coverage gaps (session strategy and review guidance are not mentioned). It exceeds the 1-2 concrete actions of the lower anchor but lacks the comprehensive coverage of the top anchor.

4 / 5

Completeness

Explicitly answers both 'what' (the three named practices) and 'when' ('Use when planning or executing engineering work that agents will carry out end to end'). The when-clause is present but is a single abstract condition rather than concrete trigger phrases, so it does not reach the top anchor.

4 / 5

Trigger Term Quality

Trigger keywords ('planning', 'executing engineering work', 'agents') are relevant but abstract, missing natural variations a user would say such as 'delegate to agents', 'AI coding workflow', or 'evals'. This fits 'some relevant keywords but missing common variations or synonyms' rather than the good-coverage anchor above.

3 / 5

Distinctiveness Conflict Risk

Distinctive niche markers like 'eval-first execution' and 'cost-aware model routing' separate it from most skills, though the broad 'planning or executing engineering work' phrase creates minor overlap risk with general planning or coding-workflow skills. Mostly distinct with minor overlap, not a fully clear niche.

4 / 5

Total

15

/

20

Passed

Validation

93%

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

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

metadata_version

'metadata.version' is missing

Warning

Total

15

/

16

Passed

Repository

affaan-m/ECC

Path

skills/agentic-engineering/SKILL.md

Reviewed

Table of Contents

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.