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/ronkupper/prism/prism-startgit clone --depth 1 https://github.com/Ronkupper/PRISMWhat 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 | $0.00032 | $0.00489 |
| Opus 5 | $0.00016 | $0.00244 |
| Sonnet 5 | $0.00006 | $0.00098 |
| Haiku 4.5 | $0.00003 | $0.00049 |
Grade A, and why
prism-start 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 2d 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.
What it actually says
Activate PRISM and begin a new engagement for the following subject — the entry point of the Setup → rounds → Closure lifecycle:
$ARGUMENTS
Then proceed:
- Load the framework. Read the PRISM Skill's core (
PRISM_core.md) in full — the operating model and architecture, the Execution Envelope / Self-check / Output triple contract, Setup mechanics, Monitors M1–M12, and Standing Principles. (Naming PRISM also triggers theprismSkill, which loads the same core; either path is fine.) - Run the SP-13 substrate self-check. Declare your model identity and confirm you are Claude, Opus-class / flagship tier (a capability floor — version-agnostic, latest by default). Halt and ask the operator on mismatch or cannot-determine.
- Run M1 (Missing Inputs) and M2 (Version Drift) against any attached Master, Lens Library, or Prompt Strategy. Halt at HIGH severity on a missing required artifact or a version mismatch.
- Begin Setup — the seven probes P1–P7 — for the subject above: grade the draft Prompt Strategy against the Lens Library toward three-layer readiness at the P0→P1 boundary, then proceed per the What's next artifact.
If the subject above is empty, ask the operator for the audit or research subject before starting Setup. If a Master for an existing engagement is attached, surface this subject against its What's next and let the operator choose rather than silently restarting Setup.
This command is a Claude-Skill convenience for invoking and seeding PRISM; it
changes no framework mechanic. The plain-language invocation ("Run a PRISM audit
on …") is equivalent and is the portable form on every other vendor. Once an
engagement is running, resume it with /prism-whats-next, fold returns back with
/prism-converge, view the trajectory with /prism-status, and finish with
/prism-close.
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.
- 2d ago First seen · 40 lines · 32 tokens per session scan A ca5cdd6b7d53
prism-start is a command published in the GitHub repository Ronkupper/PRISM (5 stars, last pushed 2mo ago), licensed MIT. It adds 32 tokens to every session and 489 once invoked, about $0.0002 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 2026-08-31.
Other commands, from other repositories
awesome-chatgpt
Search awesome-ChatGPT-repositories for open-source GitHub repositories related to ChatGPT and LLMs.
design-review
Workflow recipe — review a design end-to-end, ending in measured numbers rather than adjectives, by chaining 4 skills.
setup-pm-skills
Onboard a new user — find out what they do, recommend the right bundles & top skills, and set up a project CONTEXT.md so every skill is tailored to them.
ship-an-mcp-server
Workflow recipe — make your product agent-usable by chaining 4 skills, spec to pricing.
rescue-an-account
Workflow recipe — diagnose an at-risk customer and build the full save play through to renewal by chaining 4 skills.
report
Produce executive and technical compliance reports.