Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/shinpr/claude-code-workflows/implementation-approachnpx skills add shinpr/claude-code-workflows --skill implementation-approachgit clone --depth 1 https://github.com/shinpr/claude-code-workflowsWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00025 | $0.01873 |
| Opus 5 | $0.00013 | $0.00937 |
| Sonnet 5 | $0.00005 | $0.00375 |
| Haiku 4.5 | $0.00003 | $0.00187 |
Grade A, and why
implementation-approach scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 167 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Implementation Strategy Selection Framework (Meta-cognitive Approach)
Meta-cognitive Strategy Selection Process
Phase 1: Decision-Sufficient Current State Analysis
Core Question: "What does the existing implementation look like?"
Analysis Framework
Architecture Analysis: Responsibility separation, data flow, dependencies, technical debt
Implementation Quality Assessment: Code quality, behavior-relevant test evidence, performance, security
Historical Context Understanding: Current form rationale, past decision validity, constraint changes, requirement evolution
Meta-cognitive Question List
- What is the true responsibility of this implementation?
- Which parts are business essence and which derive from technical constraints?
- What dependencies or implicit preconditions are unclear from the code?
- What benefits and constraints does the current design bring?
Stop when another current-state fact cannot change responsibility, reuse, option validity, total complexity, a contract, or verification.
Phase 2: Design Convergence
Complete these steps in order before selecting an implementation strategy:
- Existing-Surface Baseline: Form the simplest end-to-end path that delivers the current outcome through existing responsibilities. Explicit requirements and accepted decisions are binding; suggested mechanisms remain candidates.
- Evidence Check: Test that path against current requirements, verified constraints, observed in-scope problems, and evidence-backed material risks. Keep only the unmet conditions that can change the selected design.
- Targeted Comparison: For each unmet condition, test reuse, derivation from existing data, on-demand computation, or responsibility at the current caller or boundary before adding design surface. Compare viable choices by total complexity across the dimensions that materially differ: user decisions, settings, modes, concepts, outputs, persistent state, implementation paths, UX, runtime, implementation, testing, documentation, and maintenance. Select the lowest-total-complexity choice that satisfies the condition.
- Subtraction Check: Remove each proposed addition and re-test its governing condition. Retain it only when the confirmed outcome, a required boundary, or necessary proof becomes unmet.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 3d ago First seen · 167 lines · 25 tokens per session scan A 182ac8b70d69
implementation-approach is a skill published in the GitHub repository shinpr/claude-code-workflows (675 stars, last pushed 5d ago), licensed MIT. It adds 25 tokens to every session and 1,873 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
dynamic-workflows
Ultracode / Max-Parallel mode — dynamic workflows fan work out across tens–hundreds of adversarially-verified parallel subagents for large, decomposable jobs (codebase-wide audits, big migrations, cross-checked research). Opt-in; higher token spend.
agent-teams
Experimental Agent Teams orchestration — run CCGodMode agents as parallel teammates with SharedTaskList coordination (requires CLAUDECODEEXPERIMENTALAGENTTEAMS=1).
cost-efficiency
Smart Routing — the DEFAULT CCGodMode routing policy. Risk-based, minimal-agent paths that preserve required safety gates for the changed scope.
quality-gates
Parallel quality gate orchestration — @validator and @tester run simultaneously after @builder, with mandatory decision matrix for pass/fail routing.
sprint-planning
Plan-first orchestration (ADR-004): comprehensive PLAN.md, sprint files with write-scope ownership, preflight checks, serialized integration, and the release sprint. Use for any non-trivial or multi-part request BEFORE dispatching agents.
workflows
CCGodMode Full-Gates workflow definitions — used for high-risk work and when Smart Routing escalates. Default routing is Smart Routing (skills/cost-efficiency/).