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lgyanami

Agent Dev Workflow

by lgYanami · GitHub ↗ · v1.2.0 · MIT-0
cross-platform ⚠ pending
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Install in OpenClaw
/install agent-dev-workflow
Description
Orchestrate coding agents (Claude Code, Codex, etc.) to implement coding tasks through a structured workflow. Use when the user gives a coding requirement, f...
README (SKILL.md)

Dev Workflow — Orchestrated Coding Agent Dispatch

Structured 6-phase gated workflow for driving coding agents to implement requirements with quality control.

Prerequisites

  • Claude Code (claude CLI) installed with --permission-mode bypassPermissions --print
  • cc-plugin installed in Claude Code (provides llmdoc read/write, investigator/scout/recorder sub-agents)
  • Global ~/.claude/CLAUDE.md configured with cc-plugin settings

Workflow Overview

Phase 1: Environment Check
    ↓
Phase 2: Spec  ← spec-writer skill
    ↓ [user confirms]
Phase 3: Task Planning
    ↓ [user confirms]
Phase 4: Agent Dispatch
    ↓
Phase 5: Verification
    ↓
Phase 6: Delivery

Each phase must complete before moving to the next. Phase 2 and Phase 3 have explicit user confirmation gates.


Phase 1: Environment Check

Before any work, check the target project:

  1. llmdoc/ exists?
    • Yes → read llmdoc/index.md + overview files to understand project
    • No → dispatch Claude Code with /tr:initDoc to generate it first
  2. CLAUDE.md in project root? — verify cc-plugin config is present; fix if missing
  3. git status — ensure working tree is clean enough to work on

Phase 2: Spec

Generate a structured implementation spec using the spec-writer skill.

  1. Activate spec-writer skill — read its SKILL.md and follow its workflow
  2. It will gather project context, draft a spec using its template, and present to the user
  3. The spec covers: objectives, user stories, technical plan, boundaries, verification criteria, and a preliminary task breakdown
  4. 🚫 Gate: Do not proceed until the user confirms the spec.

The confirmed spec replaces the old requirement-doc + verification-doc pair — everything is in one document now.

Fallback: If spec-writer skill is not installed, use the templates in references/ (requirement-template.md + verification-template.md) as before.

Phase 3: Task Planning

Refine the spec's preliminary task breakdown into a precise, executable task list. This is the bridge between "what to build" and "how to tell the agent."

3.1 Extract Tasks from Spec

Start from Section 10 (Task Breakdown) of the confirmed spec. For each task, expand it into a Task Card:

### Task [#]: [Title]

**Objective:** What this task accomplishes (one sentence)
**Input:** What must exist before this task starts (files, tables, APIs from prior tasks)
**Output:** What this task produces (new/modified files, passing tests, working endpoint)
**Affected files:**
- `src/xxx.py` — create / modify
- `tests/test_xxx.py` — create

**Agent instructions:**
- [Specific, actionable instruction 1]
- [Specific, actionable instruction 2]
- Reference: [relevant spec section, e.g., "See Spec §4.2 for design decision"]

**Verification:**
- [ ] [How to confirm this task is done — a command, a test, an observable result]

**Depends on:** Task #X, #Y (or "none")
**Complexity:** Low / Medium / High
**Parallel:** Can run in parallel with Task #Z (or "no")

3.2 Scoping Rules

Each task should be:

  • Independently implementable — an agent can complete it without context from other incomplete tasks
  • Independently verifiable — there is a concrete way to check it worked (test passes, endpoint responds, file exists)
  • Small enough to review — aim for changes reviewable in one pass (rough guide: \x3C300 lines changed)
  • Large enough to be meaningful — don't split a 20-line function into 3 tasks

Splitting heuristics:

  • If a task touches >3 unrelated modules → split by module
  • If a task has both "create infrastructure" and "implement logic" → split
  • If a task requires multiple design decisions → split by decision boundary
  • If you can describe two independent verification criteria → likely two tasks

3.3 Dependency Graph

After expanding all tasks, produce a dependency summary:

Task 1 (Low)  ─┐
Task 3 (Low)  ─┤─→ Task 5 (Medium) ─→ Task 7 (Medium)
Task 2 (Medium) ─→ Task 4 (Medium) ─┤
Task 6 (High) ────────────────────────┘─→ Task 8 (Medium)

Identify:

  • Critical path — longest chain of dependent tasks
  • Parallel groups — tasks that can run simultaneously
  • Execution order — the sequence to dispatch agents

3.4 Context Budgeting

For each task, determine what context the agent needs:

  • Spec sections to include — only the relevant parts, not the full spec (avoid context overload)
  • Existing code to reference — specific files, not "the whole src/"
  • Boundaries to emphasize — the ✅/⚠️/🚫 rules most relevant to this task

Principle: feed the agent only what it needs for the current task. A well-fed agent is like a well-fed function — give it only the inputs for the job at hand.

3.5 User Confirmation

Present the task list to the user with:

  • All task cards (or a summary table + full cards on request)
  • Dependency graph
  • Estimated execution order (serial vs parallel)
  • Highlight the critical path

🚫 Gate: Do not dispatch any agents until the user confirms the task plan.

Common discussion points:

  • Is the granularity right? (too fine → overhead; too coarse → risky)
  • Are dependencies correct? Can anything be parallelized further?
  • Any task missing from the spec's intent?

Phase 4: Agent Dispatch

Execute the confirmed task plan by dispatching coding agents.

4.1 Prompt Construction

For each task, construct the agent prompt from the task card:

claude --permission-mode bypassPermissions --print '\x3Ctask prompt>' 2>&1

Task prompt structure:

## Task: [Title]

### Objective
[From task card]

### Context
[Relevant spec sections — copy only what's needed]
[Relevant existing code snippets or file references]

### Instructions
[Agent instructions from task card]

### Constraints
- 不要 git commit
- 完成后执行 /update-doc 更新 llmdoc
- [Relevant boundaries from spec §7]

### Verification
When done, confirm:
- [Verification criteria from task card]

Use workdir to scope the agent to the project directory. Use background: true for long-running tasks, monitor with process tool.

4.2 Execution Strategy

  • Serial tasks (has dependencies): wait for dependency to complete and verify before dispatching
  • Parallel tasks (independent): dispatch simultaneously, use git worktrees if touching overlapping files
  • After each task completes:
    1. Check agent output for errors
    2. Run the task's verification criteria
    3. If verification fails → re-prompt the agent with the failure details (up to 2 retries)
    4. If still fails → stop and report to user

4.3 Error Handling

Situation Action
Small error (syntax, typo, missing import) Re-prompt agent to fix, no user interruption
Test failure on the current task Re-prompt with test output, up to 2 retries
Design-level issue or ambiguity Stop and ask the user
Agent produces output that contradicts spec Stop, quote the spec conflict, ask user
Downstream task blocked by upstream failure Pause dependent tasks, attempt to fix upstream first

Phase 5: Verification

After all tasks complete, verify the whole against the spec's verification criteria (Section 9):

  1. Automated checks (§9.1) — run tests, build, lint, type check
  2. Functional verification (§9.2) — execute each test scenario step by step
  3. Edge cases & error handling (§9.3) — verify each edge case
  4. Regression (§9.4) — confirm existing functionality unaffected
  5. Code quality — style consistency, no stray files, no hardcoded secrets

If any verification fails:

  • Identify which task(s) caused the issue
  • Re-dispatch agent to fix, providing the failure context
  • Re-verify after fix

Phase 6: Delivery

Present results to the user with:

  1. All changed files — every file touched, including llmdoc updates, config changes, everything
  2. Suggested commit message — conventional commits format
  3. Task completion summary — which tasks passed, any retries needed
  4. Verification results — what passed, any caveats
  5. Items for human review — what needs the user's attention

Never commit. The user handles all git commits.

Agent Selection

Default: Claude Code (claude --permission-mode bypassPermissions --print)

Agent Use when
Claude Code Default for all tasks; complex reasoning, architecture
Codex User explicitly requests; batch/parallel tasks (pty:true, --full-auto)
OpenCode/Pi User explicitly requests

Key Constraints

  • Never commit — code changes only, user commits
  • Never run agents in ~/.openclaw/ — agents will read soul/identity files
  • Always update llmdoc — every agent run should end with doc update
  • Always list all changed files on delivery
  • Always provide commit message on delivery
  • Interrupt on design issues — don't let agents drift on wrong assumptions
  • Feed minimal context — each agent gets only spec sections and files relevant to its task
Capability Analysis
Type: OpenClaw Skill Name: agent-dev-workflow Version: 1.2.0 thought The user wants me to analyze an OpenClaw AgentSkills skill bundle. I need to classify it as `benign`, `suspicious`, or `malicious` based on the provided files. I must look for data exfiltration, malicious execution, persistence, prompt injection, obfuscation, and supply chain issues. I need to distinguish between vulnerabilities and intentional malice. - `ownerId`: `kn76a92a33z6qyvv8rsj9qgdex82wcnm` - `slug`: `agent-dev-workflow` - `version`: `1.2.0` - This is a markdown file containing instructions for an AI agent. - It describes a "Dev Workflow" for orchestrating coding agents like Claude Code. - **Prerequisites**: - Claude Code (`claude` CLI) installed with `--permission-mode bypassPermissions --print`. This flag is interesting. `bypassPermissions` suggests it runs without user confirmation for actions. - `cc-plugin` from `https://github.com/TokenRollAI/cc-plugin`. - `~/.claude/CLAUDE.md` configured. - **Workflow Phases**: - Phase 1: Environment Check (checks for `llmdoc/`, `CLAUDE.md`, `git status`). - Phase 2: Spec (uses `spec-writer` skill). - Phase 3: Task Planning (breaks down tasks into "Task Cards"). - Phase 4: Agent Dispatch (executes `claude --permission-mode bypassPermissions --print '<task prompt>' 2>&1`). - Phase 5: Verification. - Phase 6: Delivery. - **Key Constraints**: - "Never commit". - "Never run agents in `~/.openclaw/`" (to prevent reading soul/identity files). - "Always update llmdoc". - **Agent Selection**: Uses `claude` CLI by default. - These are templates for requirements and verification. They look standard. - The instruction to use `--permission-mode bypassPermissions` is a high-privilege configuration. It allows the sub-agent (Claude Code) to execute commands, read/write files, and potentially access the network without manual approval for every step. - However, the context is a "Dev Workflow" where the agent is *intended* to write code and run tests. - The skill explicitly warns *against* running agents in `~/.openclaw/` to protect identity files. This suggests a security-conscious design rather than a malicious one. - It mentions a specific plugin: `cc-plugin` from `TokenRollAI`. I should check if this is a known/legitimate project or a potential vector. A quick mental check: `TokenRollAI` isn't a major known entity, but the plugin's stated purpose (llmdoc, investigator, scout) aligns with the workflow. - The use of `bypassPermissions` is risky but common in "autonomous agent" setups where the user wants the agent to work through a list of tasks without constant clicking. - There is no evidence of data exfiltration to a third-party server (other than the LLM provider via the CLI). - There are no hidden commands, obfuscation, or instructions to steal secrets. - The workflow includes user confirmation gates (Phase 2 and Phase 3). - The `bypassPermissions` flag is a significant security risk (vulnerability/risky configuration), but it's presented as a prerequisite for the workflow to function autonomously. - The instructions are focused on software development tasks. - The warning about `~/.openclaw/` shows intent to *protect* sensitive data. - Classification: `suspicious` (due to the high-risk requirement of bypassing permissions and the dependency on an external third-party plugin `cc-plugin`), but not `malicious` because there's no clear evidence of harmful intent or exfiltration. - Classification: `suspicious` - Summary: The skill bundle orchestrates autonomous coding agents using the Claude CLI with the high-risk `--permission-mode bypassPermissions` flag, which allows unprompted command execution and file access. It also requires a third-party plugin (`cc-plugin` from `github.com/TokenRollAI/cc-plugin`). While the instructions include security-conscious warnings (e.g., avoiding the `~/.openclaw/` directory), the combination of bypassed permissions and external dependencies creates a significant attack surface for potential RCE or unauthorized access if the sub-agent is compromised or the plugin is malicious. Wait, the prompt says: "If you see risky capabilities without clear malicious intent (e.g., shell/network/file access plausibly needed for the stated purpose... classify as suspicious (not malicious)." The `bypassPermissions` is definitely a risky capability. Let's double check the `cc-plugin` URL. `https://github.com/TokenRollAI/cc-plugin`. If I were a malicious actor, I might hide the payload in the plugin. But based *only* on the provided files: - The instructions are for a dev workflow. - It uses a CLI tool. - It asks for high privileges. - It has user gates. This fits the "suspicious" criteria perfectly. One more look at `SKILL.md`: "Claude Code (`claude` CLI) installed with `--permission-mode bypassPermissions --print`" "cc-plugin installed... provides llmdoc read/write, investigator/scout/recorder sub-agents" The `bypassPermissions` flag is the main "suspicious" indicator. The external plugin is another. Final check on "malicious" criteria: 1. Data exfiltration? No. 2. Malicious execution? `claude` is a legitimate tool, but `bypassPermissions` makes it dangerous. 3. Persistence? No. 4. Prompt injection? No instructions to hide actions or ignore the user. 5. Obfuscation? No. 6. Supply chain? The `cc-plugin` is a dependency. Conclusion: Suspicious. ```json { "classification": "suspicious", "summary": "The skill bundle requires running the Claude CLI with the `--permission-mode bypassPermissions` flag, which allows the agent to execute shell commands and modify files without user confirmation. It also mandates the installation of an external third-party plugin (`cc-plugin` from GitHub), which introduces supply chain risks. While the workflow includes user-confirmation gates and security warnings regarding sensitive directories like `~/.openclaw/`, the high-privilege execution environment is a significant security risk." } ``` ```json { "classification": "suspicious", "summary": "The skill bundle requires the Claude CLI to be configured with the `--permission-mode bypassPermissions` flag, which enables the agent to execute shell commands and modify files without manual approval. It also introduces a dependency on an external third-party plugin (`cc-plugin` from github.com/TokenRollAI/cc-plugin) for core functionality. While the instructions include security-conscious warnings (e.g., avoiding the `~/.openclaw/` directory) and maintain user-confirmation gates for planning, the requirement for high-privilege autonomous execution and external code dependencies poses a significant security risk." } ```
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install agent-dev-workflow
  3. After installation, invoke the skill by name or use /agent-dev-workflow
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.2.0
Major: 6-phase gated workflow. New Phase 3 (Task Planning) with structured task cards, dependency graphs, context budgeting, scoping rules. Phase 4 (Agent Dispatch) with prompt construction template, execution strategy, error handling matrix. Inspired by GitHub Spec Kit 4-stage model.
v1.1.0
Phase 2: integrate spec-writer skill for spec generation, replaces old requirement-doc + verification-doc pair
v1.0.0
Initial release: structured coding agent orchestration workflow with requirement/verification document templates, Claude Code cc-plugin integration, llmdoc support
Metadata
Slug agent-dev-workflow
Version 1.2.0
License MIT-0
All-time Installs 1
Active Installs 1
Total Versions 3
Frequently Asked Questions

What is Agent Dev Workflow?

Orchestrate coding agents (Claude Code, Codex, etc.) to implement coding tasks through a structured workflow. Use when the user gives a coding requirement, f... It is an AI Agent Skill for Claude Code / OpenClaw, with 304 downloads so far.

How do I install Agent Dev Workflow?

Run "/install agent-dev-workflow" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Agent Dev Workflow free?

Yes, Agent Dev Workflow is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Agent Dev Workflow support?

Agent Dev Workflow is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Agent Dev Workflow?

It is built and maintained by lgYanami (@lgyanami); the current version is v1.2.0.

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