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/aojdevstudio/hermes-satellite/plan-w-teamgit clone --depth 1 https://github.com/AojdevStudio/hermes-satelliteWrote 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/commands/aojdevstudio/hermes-satellite/plan-w-team)<a href="https://agentmods.dev/commands/aojdevstudio/hermes-satellite/plan-w-team"><img src="https://agentmods.dev/badge/commands/aojdevstudio/hermes-satellite/plan-w-team.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00000 | $0.03117 |
| Opus 5 | $0.00000 | $0.01558 |
| Sonnet 5 | $0.00000 | $0.00623 |
| Haiku 4.5 | $0.00000 | $0.00312 |
Grade A, and why
plan-w-team 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 5d 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.
This is a copy
100% identical to plan_w_team — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 351 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Plan With Team
Create a detailed implementation plan based on the user's requirements provided through the USER_PROMPT variable. Analyze the request, think through the implementation approach, and save a comprehensive specification document to PLAN_OUTPUT_DIRECTORY/<name-of-plan>.md that can be used as a blueprint for actual development work. Follow the Instructions and work through the Workflow to create the plan.
Variables
USER_PROMPT: $1
ORCHESTRATION_PROMPT: $2 - (Optional) Guidance for team assembly, task structure, and execution strategy
PLAN_OUTPUT_DIRECTORY: specs/
TEAM_MEMBERS: ~/.claude/agents/team/*.md
GENERAL_PURPOSE_AGENT: general-purpose
Instructions
- PLANNING ONLY: Do NOT build, write code, or deploy agents. Your only output is a plan document saved to
PLAN_OUTPUT_DIRECTORY. - If no
USER_PROMPTis provided, stop and ask the user to provide it. - If
ORCHESTRATION_PROMPTis provided, use it to guide team composition, task granularity, dependency structure, and parallel/sequential decisions. - Carefully analyze the user's requirements provided in the USER_PROMPT variable
- Determine the task type (chore|feature|refactor|fix|enhancement) and complexity (simple|medium|complex)
- Think deeply (ultrathink) about the best approach to implement the requested functionality or solve the problem
- Understand the codebase directly without subagents to understand existing patterns and architecture
- Follow the Plan Format below to create a comprehensive implementation plan
- Include all required sections and conditional sections based on task type and complexity
- Generate a descriptive, kebab-case filename based on the main topic of the plan
- Save the complete implementation plan to
PLAN_OUTPUT_DIRECTORY/<descriptive-name>.md - Ensure the plan is detailed enough that another developer could follow it to implement the solution
- Include code examples or pseudo-code where appropriate to clarify complex concepts
- Consider edge cases, error handling, and scalability concerns
- Understand your role as the team lead. Refer to the
Team Orchestrationsection for more details.
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.
- 5d ago First seen · 351 lines · 0 tokens per session scan A 07f4d8044e56
plan-w-team is a command published in the GitHub repository AojdevStudio/hermes-satellite (2 stars, last pushed 4d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 3,117 tokens. A static security scan graded it A with 0 findings. It is 100% identical to plan_w_team, differing in 2 lines, and is treated as a copy.
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.