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/atuljha23/holocron/plangit clone --depth 1 https://github.com/atuljha23/holocronWrote 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/atuljha23/holocron/plan)<a href="https://agentmods.dev/commands/atuljha23/holocron/plan"><img src="https://agentmods.dev/badge/commands/atuljha23/holocron/plan.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 | $0.00030 | $0.00354 |
| Opus 5 | $0.00015 | $0.00177 |
| Sonnet 5 | $0.00006 | $0.00071 |
| Haiku 4.5 | $0.00003 | $0.00035 |
Grade A, and why
plan 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 3d 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
/holocron:plan
Enter plan mode immediately. Do not start implementing. Use the scaffold below to organize your exploration and drafted plan.
If the user provided a task in $ARGUMENTS, treat that as the objective. Otherwise, ask what they want to accomplish.
Plan scaffold to fill in
## Context
<one paragraph: what problem this solves, what the trigger was, what outcome defines success>
## Success criteria
- [ ] <concrete, testable criterion 1>
- [ ] <concrete, testable criterion 2>
- [ ] ...
## Out of scope
- <explicit non-goals>
## Approach
<2-3 sentences: the chosen shape. If there are alternative shapes worth naming, do so and say why this one wins.>
## Files to touch
- <path>:<short note>
- ...
## Risks
- <risk>: <mitigation>
## Verification
- <how we confirm this works end-to-end; ideally a test or a command to run>
## Rollback
<how we undo this if it breaks production, if applicable>
Rules
- Read before planning. Cite specific files and functions you'll touch.
- Name tradeoffs explicitly. If you're uncertain between two shapes, ask via AskUserQuestion.
- Keep the plan short enough to scan, detailed enough to execute.
- When ready, call
ExitPlanModeto present it for approval.
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.
- 3d ago First seen · 50 lines · 30 tokens per session scan A 61a1b73c610d
plan is a command published in the GitHub repository atuljha23/holocron (2 stars, last pushed 4mo ago), licensed MIT. It adds 30 tokens to every session and 354 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.
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commit
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skill-optimize
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