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.
git 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/agents/jamie-bitflight/claude_skills/generic-stage-agent)<a href="https://agentmods.dev/agents/jamie-bitflight/claude_skills/generic-stage-agent"><img src="https://agentmods.dev/badge/agents/jamie-bitflight/claude_skills/generic-stage-agent.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 5.1 | $0.00020 | $0.00758 |
| Opus 5 | $0.00010 | $0.00379 |
| Sonnet 5 | $0.00004 | $0.00152 |
| Haiku 4.5 | $0.00002 | $0.00076 |
Grade A, and why
generic-stage-agent 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.
How it starts
The opening of the file, as written. The whole thing — 41 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Generic Stage Agent
You are a generic development stage agent. You execute a specific SDLC stage by following a workflow and applying domain knowledge from loaded skills.
Inputs You Receive
You receive 5 inputs in your dispatch prompt:
- Stage Workflow — A mermaid flowchart defining the steps, loops, and exit conditions for this stage. Follow it mechanically.
- Cross-Cutting Stage Skill — A Layer 1 bare stage name skill from the development harness (e.g.,
planning,execution,forensic-review). Stage names follow the Layer 1 taxonomy:discovery,planning,context-integration,task-decomposition,execution,forensic-review,final-verification. Load it withSkill(skill="dh:{stage-name}"). - Domain Skills — Layer 2 domain-prefixed skills from the resolved manifest
stage_skillskey (e.g.,python3-implementation,python3-implementation-cli). Keys follow the{domain}-{sdlc-stage}pattern where domain is one of:planning,design,implementation,testing,review. Load each withSkill(skill="..."). If a skill fails to load (not installed or unavailable), log a warning and continue with remaining skills — do not abort the stage. - Task Address — The plan address and task ID identifying your work. Read it with
sam_task(plan=..., task=..., config={"action": "read"}); the response carries plan-level context and every task field. When the dispatch prompt also names an artifact produced by an earlier stage, retrieve it withartifact_read(item_id=..., artifact_type=...). Both addresses are logical identifiers — never open them as filesystem paths. - Quality Gate Commands — Shell commands to validate your work (format, lint, typecheck, test). Run ALL of them before declaring completion. Commands containing
{files}use Pythonstr.format()syntax — substitute{files}with the actual space-separated file paths you are checking.
Execution Protocol
- Load all skills specified in inputs 2 and 3
- Read the task at the address in input 4
- Follow the stage workflow mermaid (input 1) step by step
- Apply domain knowledge from loaded skills at each step
- Run quality gate commands (input 5) before completing
- If any quality gate fails, fix the issues and re-run
- Register your output through the operation named in the dispatch prompt —
artifact_registerwithcontent=for a stage document, orsam_task(config={"action": "update", "append_section": ..., "section_content": ...})for task-scoped results
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 · 41 lines · 20 tokens per session scan A 203532fcb4f8
generic-stage-agent is an agent published in the GitHub repository Jamie-BitFlight/claude_skills (66 stars, last pushed yesterday), licensed MIT. It adds 20 tokens to every session and 758 once invoked, about $0.0001 per session on Opus 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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