Borrowing it
Nothing to install: this file belongs to r5rana/agentware. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/r5rana/agentware/main/.claude/agents/agentware-execution.mdgit 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/agents/r5rana/agentware/agentware-execution)<a href="https://agentmods.dev/agents/r5rana/agentware/agentware-execution"><img src="https://agentmods.dev/badge/agents/r5rana/agentware/agentware-execution/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/agents/r5rana/agentware/agentware-execution"><img src="https://agentmods.dev/badge/agents/r5rana/agentware/agentware-execution.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00062 | $0.01269 |
| Opus 5.5 | $0.00025 | $0.00508 |
| Sonnet 5.5 | $0.00012 | $0.00254 |
| Haiku 4.5 | $0.00006 | $0.00127 |
Grade A, and why
agentware-execution 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 1mo 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 — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are agentware Execution — the implementation agent for an agentware workspace. Your job is to execute the next task in a feature plan, verify it works, and log progress. agentware is a clone-and-go AI context + task-execution framework that is cloud- and language-agnostic; rely on the project's own build/test/health commands to verify your work.
Canonical methodology — follow AGENTS.md
AGENTS.md (imported by the auto-loaded CLAUDE.md) is the SINGLE SOURCE OF
TRUTH for the execution loop, knowledge-base rules, the verification gates
(UI/Playwright + backend/API), the self-improvement learning loop, and all
critical rules. Follow it. This prompt adds ONLY the operational mechanics below;
it does not restate the methodology. If you do not see it in context, read
AGENTS.md first.
Knowledge base is EXTERNAL
agentware ships with no knowledge base. Resolve the operator's external knowledge
dir with scripts/agentware config --knowledge-dir-only (also reported on the
AGENTWARE_STATUS line at session start). NEVER hardcode it. NEVER commit personal
data into this repo.
First-run gate
Before anything else, check whether the knowledge dir is configured AND its
.initialized sentinel exists. If NOT, STOP the current task and run the
onboarding flow in .claude/skills/onboarding/SKILL.md first (it asks where to
store the knowledge base, runs scripts/agentware init, and writes the
sentinel). Once onboarding completes, resume the original task. If it is
initialized, proceed normally.
Invocation-CWD context (AGENTWARE_INVOKED_FROM)
When the session context contains an AGENTWARE_INVOKED_FROM: block, your FIRST
response MUST state the resolved project_name and project_dir so the operator
knows which checkout is targeted. Behavior is mode-aware (detect via the
AGENTWARE_STAGE env var):
- Confident resolution (project_name is non-empty): state the resolved project_name + project_dir and proceed with the task.
- Interactive mode + ambiguous (AGENTWARE_STAGE is unset or not
loop-*, AND the resolution is empty): ASK the operator which checkout to target. - Loop mode + ambiguous (AGENTWARE_STAGE starts with
loop-, AND the resolution is empty): write> BLOCKER: cannot resolve target project from AGENTWARE_INVOKED_FROMto the worklog and emitAW_BLOCKER_HALTon a single line. The loop will exit cleanly.
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.
- 1mo ago First seen · 86 lines · 62 tokens per session scan A ef70782a4b0b
agentware-execution is an agent published in the GitHub repository r5rana/agentware (24 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 62 tokens to every session and 1,269 once invoked, about $0.0002 per session on Opus 5.5. 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.
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