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 skills add vasilyu1983/AI-Agents-public --skill dev-workflow-planninggit clone --depth 1 https://github.com/vasilyu1983/AI-Agents-publicWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/vasilyu1983/ai-agents-public/dev-workflow-planning)<a href="https://agentmods.dev/skills/vasilyu1983/ai-agents-public/dev-workflow-planning"><img src="https://agentmods.dev/badge/skills/vasilyu1983/ai-agents-public/dev-workflow-planning/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/vasilyu1983/ai-agents-public/dev-workflow-planning"><img src="https://agentmods.dev/badge/skills/vasilyu1983/ai-agents-public/dev-workflow-planning.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Agent Snooping · line 221 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
What 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 5.1 | $0.00037 | $0.05489 |
| Opus 5 | $0.00018 | $0.02745 |
| Sonnet 5 | $0.00007 | $0.01098 |
| Haiku 4.5 | $0.00004 | $0.00549 |
Grade A, and why
dev-workflow-planning 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 9d 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 — 282 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Dev Workflow Planning
Use this skill to turn vague or risky engineering work into a bounded execution plan with scope, sequencing, checkpoints, verification, and handoff. It owns planning depth, execution shape, and multi-agent guardrails, not system design, PRD authoring, or branch-policy decisions.
Quick Reference
| Task | Use |
|---|---|
| Plan structures and artifacts | references/planning-templates.md, assets/template-work-item-ticket.md, assets/template-milestone-checkpoint.md, assets/template-dor-dod.md |
| Platform-specific workflow mapping | references/platform-workflows.md, ../ai-agents/references/agent-delivery-methods.md |
| Guardrails for parallelism, sessions, and recovery | references/operational-checklists.md, references/session-patterns.md, references/session-scope-budgeting.md, ../ai-agents/references/context-rotation-and-state.md |
| Spec-driven tooling landscape (GitHub Spec Kit, Kiro, BMAD) | references/spec-driven-dev-landscape.md |
| Test-context planning | ../qa-agent-testing/references/coding-agent-regression-testing.md |
| Source map | data/sources.json |
When to Use
- Break a feature, migration, refactor, or risky bug fix into verified steps.
- Decide whether work should run sequentially or in bounded parallel waves.
- Turn a requirement or RFC into a plan contract with success criteria and rollback thinking.
- Keep long-running agent work inside durable artifacts and scope limits.
Route Elsewhere
What ships with it
18 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- agents/openai.yaml 361 B
- assets/example-medium-plan-contract.md 8.1 KB
- assets/template-dor-dod.md 9.6 KB
- assets/template-milestone-checkpoint.md 862 B
- assets/template-work-item-ticket.md 2.1 KB
- data/sources.json 12 KB
- learnings.consolidated.md 597 B
- learnings.md 1.4 KB
- references/agile-ceremony-patterns.md 13 KB
- references/flow-metrics.md 4.2 KB
- references/operational-checklists.md 5.3 KB
- references/planning-templates.md 10.0 KB
- references/platform-workflows.md 5.5 KB
- references/remote-async-workflows.md 17 KB
- references/session-patterns.md 4.5 KB
- references/session-scope-budgeting.md 823 B
- references/spec-driven-dev-landscape.md 3.3 KB
- references/technical-debt-management.md 15 KB
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.
- 9d ago First seen · 282 lines · 37 tokens per session scan A 76a62ede44ed
dev-workflow-planning is a skill published in the GitHub repository vasilyu1983/AI-Agents-public (87 stars, last pushed 7d ago), licensed MIT. It adds 37 tokens to every session and 5,489 once invoked, about $0.0002 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
nft-standards
Implement NFT standards (ERC-721, ERC-1155) with proper metadata handling, minting strategies, and marketplace integration. Use when creating NFT contracts, building NFT marketplaces, or implementing digital asset systems.
istio-traffic-management
Configure Istio traffic management including routing, load balancing, circuit breakers, and canary deployments. Use when implementing service mesh traffic policies, progressive delivery, or resilience patterns.
projection-patterns
Build read models and projections from event streams. Use when implementing CQRS read sides, building materialized views, or optimizing query performance in event-sourced systems.
microservices-patterns
Design microservices architectures with service boundaries, event-driven communication, and resilience patterns. Use when building distributed systems, decomposing monoliths, or implementing microservices.
track-management
Use this skill when creating, managing, or working with Conductor tracks - the logical work units for features, bugs, and refactors. Applies to spec.md, plan.md, and track lifecycle operations.
plan-validate
Deterministic plan.json validation via Python script, replacing most plan-validator agent calls. Performs JSON parsing, schema validation, task checkbox regex, required section checks, sync validation, and data extraction. Only semantic consistency checks (storage/query alignment) require the LLM agent. Triggers on…