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 commands/varunk130/ai-workflow-playbooks/constructgit clone --depth 1 https://github.com/varunk130/ai-workflow-playbooksWhat 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 | $0.00000 | $0.00130 |
| Opus 5 | $0.00000 | $0.00065 |
| Sonnet 5 | $0.00000 | $0.00026 |
| Haiku 4.5 | $0.00000 | $0.00013 |
Grade A, and why
construct 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 2d 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.
What it actually says
Run the CONSTRUCT stage of the AI Workflow Playbooks pipeline.
Load and execute these playbooks together:
playbooks/iterative-construction/PLAYBOOK.md- Build in thin vertical slices with continuous verificationplaybooks/test-first-engineering/PLAYBOOK.md- Write tests before implementation code
For each task in the implementation sequence:
- Write a failing test that captures the expected behavior
- Implement the minimum code to make the test pass
- Refactor for clarity while keeping tests green
- Commit after each completed task
Verify all tests pass and no regressions are introduced before marking a task complete.
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.
- 2d ago First seen · 14 lines · 0 tokens per session scan A e8ee7b86799f
construct is a command published in the GitHub repository varunk130/ai-workflow-playbooks (2 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 130 tokens. 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 2026-08-31.
Other commands, from other repositories
derive-tests
Turn documented intent into a test-coverage map — inventory the tests that exist today, derive use-case cases from the system docs, separate existing coverage from proposed tests and unverified gaps, mark each unit / guarded-live / manual, and recommend a green-before-merge CI gate.
ship-check
Turn a vibe-coded repo into a reviewer-ready shipping packet — document the app, wire agent context, run security and performance audits, map test coverage, and compile the results.
plan-launch
Create a full go-to-market strategy — beachhead segment, ICP, messaging, channels, and launch plan.
competitive-analysis
Analyze the competitive landscape — identify competitors, compare strengths and weaknesses, find differentiation opportunities.
tdd-requirements
TDD開発の要件整理を行います。機能要件を明確化し、テスト駆動開発のための準備を行います。.
go-test
Go TDD workflow with table-driven tests.