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 rules/rajitsaha/100xprism/prgit clone --depth 1 https://github.com/rajitsaha/100xprismWrote 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/rules/rajitsaha/100xprism/pr)<a href="https://agentmods.dev/rules/rajitsaha/100xprism/pr"><img src="https://agentmods.dev/badge/rules/rajitsaha/100xprism/pr.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 | $0.00010 | $0.01045 |
| Opus 5 | $0.00005 | $0.00522 |
| Sonnet 5 | $0.00002 | $0.00209 |
| Haiku 4.5 | $0.00001 | $0.00104 |
Grade A, and why
pr scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 192 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PR — Create Pull Request with AI Review
Create a GitHub Pull Request with full AI review. Human approves and merges — do NOT merge automatically; always stop after PR creation and AI review.
Step 0 — Smart default: ensure feature branch
PROJECT_ROOT=$(git rev-parse --show-toplevel)
cd "$PROJECT_ROOT"
DEFAULT_BRANCH=$(git symbolic-ref refs/remotes/origin/HEAD 2>/dev/null | sed 's@^refs/remotes/origin/@@')
DEFAULT_BRANCH="${DEFAULT_BRANCH:-main}"
CURRENT_BRANCH=$(git branch --show-current)
If on the default branch: Run the branch workflow first to create a feature branch. Then continue.
If on a feature branch: Continue with PR creation.
Phase 1 — Pre-flight
Run the gate workflow. All gates must pass before creating a PR (Gates 1–3 always; Gates 4–5 when applicable).
If any gate fails → STOP. Fix issues first. Do NOT create a PR with failing gates.
Phase 2 — Push branch
git push -u origin "$CURRENT_BRANCH"
Phase 3 — Generate PR content
Title
- Derive from branch name and commit messages
- Under 70 characters
- Use conventional format:
feat: add user authentication
Body
Generate from the diff against the default branch:
git log "$DEFAULT_BRANCH"..HEAD --oneline
git diff "$DEFAULT_BRANCH"...HEAD --stat
Structure the body as:
## Summary
- [2-3 bullet points describing what changed and why]
## Changes
- [list of key files/areas modified]
## Test plan
- [ ] [How this was tested]
- [ ] [What to verify during review]
## Related issues
[Auto-detected from commit messages: "fixes #42", "closes #13", etc.]
Phase 4 — Create PR
gh pr create \
--title "<generated title>" \
--body "<generated body>" \
--base "$DEFAULT_BRANCH" \
--head "$CURRENT_BRANCH"
Capture the PR number and URL from the output.
Phase 5 — AI Review
Review the full diff and post findings as a PR comment.
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 · 192 lines · 10 tokens per session scan A 8f7fbc6a5c48
pr is a cursor rule published in the GitHub repository rajitsaha/100xprism (10 stars, last pushed 6d ago), licensed MIT. It adds 10 tokens to every session and 1,045 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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