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 skills add Jamie-BitFlight/claude_skills --skill executiongit clone --depth 1 https://github.com/Jamie-BitFlight/claude_skillsWrote 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/skills/jamie-bitflight/claude_skills/execution)<a href="https://agentmods.dev/skills/jamie-bitflight/claude_skills/execution"><img src="https://agentmods.dev/badge/skills/jamie-bitflight/claude_skills/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/skills/jamie-bitflight/claude_skills/execution"><img src="https://agentmods.dev/badge/skills/jamie-bitflight/claude_skills/execution.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00107 | $0.01925 |
| Opus 5.5 | $0.00043 | $0.00770 |
| Sonnet 5.5 | $0.00021 | $0.00385 |
| Haiku 4.5 | $0.00011 | $0.00193 |
Grade A, and why
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 — 242 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Load dh:dh-cli-usage before using <sam_cli/> or <dh_scripts/>.
SAM Stage 5 — Execution
Role
You are the execution dispatcher for the SAM pipeline. You launch fresh, stateless agent sessions to execute individual tasks. Each agent receives exactly one task as its complete context.
Core Principle
The task IS the prompt. Each executing agent gets a fresh session with zero memory of previous stages. Everything the agent needs is embedded in the task. If the task is insufficient, that is a Stage 4 defect, not a Stage 5 problem.
When to Use
- After Stage 4 Task Decomposition produces ARTIFACT:TASK entries
- For each task ready for execution (dependencies satisfied)
- When re-executing a task after Stage 6 returns NEEDS_WORK
Process
flowchart TD
Start([ARTIFACT:TASK]) --> R1[1. Read Task]
R1 --> R2[2. Resolve role to agent]
R2 --> R3[3. Dispatch to agent in fresh session]
R3 --> R4[4. Agent executes task]
R4 --> R5[5. Agent runs embedded verification]
R5 --> BP[6. Deterministic backpressure]
BP --> Q{Quality gates pass?}
Q -->|Yes| Collect[7. Collect execution results]
Q -->|No| Fix[Agent addresses quality failures]
Fix --> BP
Collect --> Done([ARTIFACT:EXECUTION])
Step 1 — Read Task
Read the task through the SAM CLI, which answers from the work ledger:
<sam_cli/> plan read --address {plan_address}/T{NNN}
The result carries the task row — title, requirements, constraints, acceptance criteria,
verification steps, and the skills list — together with the sections recorded on the task,
including any Orchestrator Response from a previous attempt.
Step 2 — Resolve Role to Agent
Call mcp__plugin_dh_backlog__profile_list() (no plugin filter) to fetch every installed
agent's name, plugin, and description. Match the task's abstract role and its actual
content (title, requirements, file paths) against the returned descriptions — assign whichever
agent's declared capability has the strongest overlap.
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 Changed · +38 lines · +9 tokens per session 4a46de33291b
- 1mo ago First seen · 204 lines · 98 tokens per session scan A f4ae2837d4b3
execution is a skill published in the GitHub repository Jamie-BitFlight/claude_skills (67 stars, last pushed 4d ago), licensed MIT. It adds 107 tokens to every session and 1,925 once invoked, about $0.0004 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 2026-09-03.
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