Source profileQuality 65/100
affaan-m/ECC/skills/agentic-engineering/SKILL.md
agentic-engineering
Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing.
- Source repository stars
- 234,327
- Declared platforms
- 0
- Static risk flags
- 0
- Last source update
- 2026-07-27
- Source checked
- 2026-07-28
Decision brief
What it does—and where it fits
Use this skill for engineering workflows where AI agents perform most implementation work and humans enforce quality and risk controls.
Not for
- Tasks that require unconfirmed production actions or broad system permissions.
- Environments where the pinned source and install steps cannot be inspected.
Compatibility matrix
Platform support, with evidence labels
| Platform | Status | Evidence | What to check |
|---|---|---|---|
| Codex | Not declared | No explicit evidence | Portability before use |
| Claude Code | Not declared | No explicit evidence | Portability before use |
| Cursor | Not declared | No explicit evidence | Portability before use |
| Gemini CLI | Not declared | No explicit evidence | Portability before use |
Installation
Inspect first. Install second.
The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.
Source-detected install commandSource
npx skills add https://github.com/affaan-m/ECC --skill "skills/agentic-engineering"Safe inspection promptEditorial
Inspect the Agent Skill "agentic-engineering" from https://github.com/affaan-m/ECC/blob/4e973d3eaf92d97f8d2e2d8abb39d8bdc8711b38/skills/agentic-engineering/SKILL.md at commit 4e973d3eaf92d97f8d2e2d8abb39d8bdc8711b38. List every install step, command, network request, credential, file read/write, external action, and rollback step. Explain whether it fits my task. Do not install or execute anything until I approve.
Workflow
What the source asks the agent to do
- 01
Review Focus for AI-Generated Code
Prioritize: - invariants and edge cases - error boundaries - security and auth assumptions - hidden coupling and rollout risk
invariants and edge caseserror boundariessecurity and auth assumptions - 02
Operating Principles
1. Define completion criteria before execution. 2. Decompose work into agent-sized units. 3. Route model tiers by task complexity. 4. Measure with evals and regression checks.
Define completion criteria before execution.Decompose work into agent-sized units.Route model tiers by task complexity. - 03
Eval-First Loop
1. Define capability eval and regression eval. 2. Run baseline and capture failure signatures. 3. Execute implementation. 4. Re-run evals and compare deltas.
Define capability eval and regression eval.Run baseline and capture failure signatures.Execute implementation. - 04
Task Decomposition
Apply the 15-minute unit rule: - each unit should be independently verifiable - each unit should have a single dominant risk - each unit should expose a clear done condition
each unit should be independently verifiableeach unit should have a single dominant riskeach unit should expose a clear done condition
Permission review
Static risk signals and limitations
No configured static risk pattern was detected
This is not proof of safety. Runtime behavior, indirect dependencies, and hidden external systems are outside the static scan.
Evidence record
Why each signal appears
EvidenceSourceComputedTestedEditorial
| Signal | Value | Evidence type | Meaning |
|---|---|---|---|
| Quality score | 65/100 | Computed | Documentation, specificity, maintenance, and trust rules |
| Repository stars | 234,327 | Source | Repository attention, not individual Skill quality |
| Compatibility | 0 platforms | Source | Declared in the catalog source record |
| Usage guide | automated source guide | Editorial | Generated or reviewed according to the visible evidence level |
Pinned source
Provenance and original SKILL.md
- Repository
- affaan-m/ECC
- Skill path
- skills/agentic-engineering/SKILL.md
- Commit
- 4e973d3eaf92d97f8d2e2d8abb39d8bdc8711b38
- License
- MIT
- Collected
- 2026-07-28
- Default branch
- main
View the original SKILL.md
Agentic Engineering
Use this skill for engineering workflows where AI agents perform most implementation work and humans enforce quality and risk controls.
Operating Principles
- Define completion criteria before execution.
- Decompose work into agent-sized units.
- Route model tiers by task complexity.
- Measure with evals and regression checks.
Eval-First Loop
- Define capability eval and regression eval.
- Run baseline and capture failure signatures.
- Execute implementation.
- Re-run evals and compare deltas.
Task Decomposition
Apply the 15-minute unit rule:
- each unit should be independently verifiable
- each unit should have a single dominant risk
- each unit should expose a clear done condition
Model Routing
- Haiku: classification, boilerplate transforms, narrow edits
- Sonnet: implementation and refactors
- Opus: architecture, root-cause analysis, multi-file invariants
Session Strategy
- Continue session for closely-coupled units.
- Start fresh session after major phase transitions.
- Compact after milestone completion, not during active debugging.
Review Focus for AI-Generated Code
Prioritize:
- invariants and edge cases
- error boundaries
- security and auth assumptions
- hidden coupling and rollout risk
Do not waste review cycles on style-only disagreements when automated format/lint already enforce style.
Cost Discipline
Track per task:
- model
- token estimate
- retries
- wall-clock time
- success/failure
Escalate model tier only when lower tier fails with a clear reasoning gap.
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When the user wants to plan, design, or implement an A/B test or experiment, or build a growth experimentation program. Also use when the user mentions "A/B test," "split test," "experiment," "test this change," "variant copy," "multivariate test," "hypothesis," "should I test this," "which version is better," "test two versions," "statistical significance," "how long should I run this test," "growth experiments," "experiment velocity," "experiment backlog," "ICE score," "experimentation program