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 skills/ai-driven-dev/framework/00-sdlcnpx skills add ai-driven-dev/framework --skill 00-sdlcgit clone --depth 1 https://github.com/ai-driven-dev/frameworkWhat 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 | $0.00076 | $0.02237 |
| Opus 5 | $0.00038 | $0.01118 |
| Sonnet 5 | $0.00015 | $0.00447 |
| Haiku 4.5 | $0.00008 | $0.00224 |
Grade A, and why
aidd-dev:00:sdlc 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 yesterday.
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 — 147 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: sdlc
Pure orchestrator. Takes a free-form request and drives it through spec → plan → implementation → done by composing other skills and agents. This skill is a workflow descriptor: every step delegates to a skill or an agent. No business logic lives here.
Iron rule
You are the conductor, not a player.
You never write code. You never run tests. You never commit. You never load a skill into your own context.
Every action — including invoking another skill — is delegated to a sub-agent that runs in a fresh context. You only ever read structured outputs (YAML) returned by sub-agents. You never read the contents of files produced (spec.md, plan.md, source code) — those belong to the agents that wrote them.
If you find yourself about to use the Skill, Write, Edit, Bash tool yourself for anything other than reading a sub-agent output or routing it to the next phase, you have violated the protocol. Stop and re-delegate.
Skill invocation protocol
You never call Skill(...) directly. Every skill invocation is wrapped in an Agent spawn:
-
Spawn the Agent tool with
subagent_type: general-purpose. -
Prompt template:
Invoke skill `<skill-id>` with these inputs: <yaml inputs> Run the skill in your fresh context. When done, return ONLY the structured output described by the skill's frontmatter, in YAML, with no surrounding prose. Do not include the file contents you produced. -
Parse the agent's YAML response. Use the values, not the produced content.
This applies to: aidd-pm:05:spec, aidd-vcs:01:commit, aidd-vcs:02:pull-request. Skills used by planner, implementer, or reviewer are loaded inside those agents' own contexts — that already satisfies the rule.
When to use
- A human invokes
/sdlc <request>to start a new run from a free-form description - A Gardener (async) decides a new run is needed and invokes this skill
- A previous run was paused and needs to be resumed with refined input
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.
- yesterday First seen · 147 lines · 76 tokens per session scan A 19bd4a8cf8c6
aidd-dev:00:sdlc is a skill published in the GitHub repository ai-driven-dev/framework (445 stars, last pushed yesterday), licensed MIT. It adds 76 tokens to every session and 2,237 once invoked, about $0.0004 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 2026-08-30.
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