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/sunbird-knowlg/knowledge-platform/prgit clone --depth 1 https://github.com/Sunbird-Knowlg/knowledge-platformWrote 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/commands/sunbird-knowlg/knowledge-platform/pr)<a href="https://agentmods.dev/commands/sunbird-knowlg/knowledge-platform/pr"><img src="https://agentmods.dev/badge/commands/sunbird-knowlg/knowledge-platform/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 | $0.00014 | $0.00378 |
| Opus 5 | $0.00007 | $0.00189 |
| Sonnet 5 | $0.00003 | $0.00076 |
| Haiku 4.5 | $0.00001 | $0.00038 |
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 today.
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
Open a pull request for knowledge-platform. Base branch = $1 (default develop if empty).
Context
Current branch:
!git branch --show-current
Recent commits on this branch:
!git log --oneline -15
PR template:
!cat .github/pull_request_template.md
Steps
- Resolve the base ref: use
${1:-develop}if it exists locally, elseorigin/${1:-develop}(rungit fetch origin ${1:-develop}first if needed). Then list the branch's commits and changed files vs that base:git log <base>..HEAD --onelineandgit diff --stat <base>...HEAD. If there are no commits ahead, stop and say so. - Draft the PR title as a Conventional Commits summary of the branch.
- Fill the PR template sections from the commits/diff: summary + issue reference, tick the correct Type of change box, describe How Has This Been Tested?, and complete the checklist honestly.
- Confirm the title and body with the user, then create it:
gh pr create --base ${1:-develop} --head <current-branch> --title "<title>" --body "<body>" - Report the PR URL.
Push the branch first if gh reports the head branch isn't on the remote (ask before pushing).
Examples
/pr # open a PR against develop (default)
/pr release-1.0 # open a PR against release-1.0
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.
- today First seen · 37 lines · 14 tokens per session scan A 657acec69c2e
pr is a command published in the GitHub repository Sunbird-Knowlg/knowledge-platform (17 stars, last pushed yesterday), licensed MIT. It adds 14 tokens to every session and 378 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 2026-09-04.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.