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/r5rana/agentware/agentware-plangit clone --depth 1 https://github.com/r5rana/agentwareWrote 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/r5rana/agentware/agentware-plan)<a href="https://agentmods.dev/commands/r5rana/agentware/agentware-plan"><img src="https://agentmods.dev/badge/commands/r5rana/agentware/agentware-plan.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 | $0.00476 |
| Opus 5 | $0.00000 | $0.00238 |
| Sonnet 5 | $0.00000 | $0.00095 |
| Haiku 4.5 | $0.00000 | $0.00048 |
Grade A, and why
agentware-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 3d 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 — 45 lines — stays where its author put it; the contents beside it link to each section on GitHub.
@agentware-plan
Create a new feature plan for the loop to execute in this agentware workspace.
Instructions
- Read
docs/loop.mdto understand how to create plan and design documents. - Read
AGENTS.mdfor the project's execution methodology. - Read the knowledge base MAIN.md (resolve its dir via
scripts/agentware config --knowledge-dir-only) for current active work. - Ask the user for the feature requirements (3–5 targeted questions max).
- Determine which task types are involved:
- infra — environment / resource provisioning using the project's own tooling (no assumed cloud verbs).
- code — code changes in this workspace or a sibling workspace.
- config — configuration changes deployed to running services.
- knowledge — knowledge-base updates (entries,
index.json,MAIN.md).
- Create a docs directory:
<knowledge-dir>/work/<YYMMDD-feature-name>/. - Write
plan.mdwith phases, tasks, and acceptance criteria following the format indocs/loop.md. - Optionally create
design.mdfor complex features. - Tell the user which folder you created the files in.
- Suggest the user run
./agentware.sh <feature-name>to execute the plan, or re-run the planner to iterate.
Task scoping guidelines
- Each task should be one logical unit of work.
- Infrastructure tasks: one resource per task.
- Knowledge-base tasks: group related updates (e.g. "Create project entry +
update
index.json"). - Cross-workspace code tasks: one coherent change per task.
- Every task MUST have verifiable acceptance criteria expressed in the project's own commands.
Conventions for plan content
- Naming:
{project}-{resource}-v{version}unless the project documents its own. - Relative paths inside repo files; resolve the external knowledge dir at runtime.
- Verification: each task lists a concrete check (file exists, test passes, command output, etc.).
- Always include a knowledge-base-update task in the final phase.
- Set the promise tag at the top of the plan:
<promise>YYMMDD_FEATURE_NAME_COMPLETE</promise>.
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.
- 3d ago First seen · 45 lines · 0 tokens per session scan A 49788e63bf89
agentware-plan is a command published in the GitHub repository r5rana/agentware (24 stars, last pushed 16d ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 476 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 2026-08-30.
Other commands, from other repositories
git
Git operations with intelligent commit messages and workflow optimization.
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.