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/pipekit/mcp-for-argo-workflows/implement-plangit clone --depth 1 https://github.com/pipekit/mcp-for-argo-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 | $0.00000 | $0.00624 |
| Opus 5 | $0.00000 | $0.00312 |
| Sonnet 5 | $0.00000 | $0.00125 |
| Haiku 4.5 | $0.00000 | $0.00062 |
Grade A, and why
implement-plan 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 yesterday.
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 — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Implement Plan from Linear
You are orchestrating the implementation of the mcp-for-argo-workflows project based on the Linear project plan.
Step 1: Fetch Current State from Linear
First, retrieve the current project status:
- Use
mcp__linear-server__list_issueswithproject: "mcp-for-argo-workflows"to get all issues - Identify issues by status: Backlog, Todo, In Progress, Done
- Check issue dependencies (noted in each issue's description)
Step 2: Identify Ready Tasks
Analyze the issues to find tasks that are ready to implement:
- Setup tasks (PIP-5 through PIP-14) - Foundation work, check dependencies
- MCP tools (PIP-15 through PIP-49) - Require setup tasks complete
- Testing (PIP-50, PIP-51) - Require tools implemented
- Documentation (PIP-9, PIP-52, PIP-53) - Can be done incrementally
A task is "ready" when:
- Status is Backlog or Todo
- All dependencies (listed in issue description) are completed
Step 3: Present Ready Tasks
Present the list of ready tasks to the user with:
- Issue identifier (e.g., PIP-10)
- Title
- Brief description of what it involves
- Dependencies (and their status)
Step 4: Execute Implementation via /implement-issue
For each ready task, use the /implement-issue command to implement it:
/implement-issue PIP-XX
IMPORTANT: Always use /implement-issue to implement individual tasks. This ensures consistent implementation workflow across all tasks.
Wait for each task to complete before starting the next one.
Step 5: Report Progress
After each implementation cycle:
- Summarize what was completed
- List any blockers or issues encountered
- Identify next tasks ready for implementation (dependencies now met)
- Ask user if they want to continue with the next task
Implementation Guidelines
- One task at a time - Complete and verify before moving to next
- Always use /implement-issue - Never implement tasks directly in this command
- Ask for clarification - If requirements are ambiguous, ask before implementing
- Report blockers - If a task cannot be completed, report why and suggest alternatives
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.
- yesterday First seen · 76 lines · 0 tokens per session scan A fe289b4291da
implement-plan is a command published in the GitHub repository pipekit/mcp-for-argo-workflows (5 stars, last pushed 2d ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 624 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
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.