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/nickmisasi/planner/spikenpx skills add nickmisasi/planner --skill spikegit clone --depth 1 https://github.com/nickmisasi/plannerWrote 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/skills/nickmisasi/planner/spike)<a href="https://agentmods.dev/skills/nickmisasi/planner/spike"><img src="https://agentmods.dev/badge/skills/nickmisasi/planner/spike.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 | $0.00035 | $0.00686 |
| Opus 5 | $0.00017 | $0.00343 |
| Sonnet 5 | $0.00007 | $0.00137 |
| Haiku 4.5 | $0.00003 | $0.00069 |
Grade A, and why
spike 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.
How it starts
The opening of the file, as written. The whole thing — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Set up and run a focused experiment to validate an assumption or test a theory.
Instructions
When the user invokes /spike, follow these steps:
1. Ensure Context is Loaded
The spike should be related to a current idea. If no idea is active, trigger /continue first.
2. Define the Spike
Use AskUserQuestion to clarify:
- Question to answer — What specific assumption or theory are we testing?
- Approach — How will we test it? (API call, prototype code, config test, etc.)
- Success criteria — What result would validate or invalidate the assumption?
- Time box — How much effort is appropriate? (quick test, small prototype, deeper investigation)
3. Scaffold the Spike
Use the planning CLI to create the spike directory and README:
python3 bin/planning new-spike \
--project <project-slug> \
--idea <idea-slug> \
--name "Spike Name" \
--slug spike-slug \
--question "What are we trying to find out?" \
--approach "How we will test it" \
--criteria "What result we are looking for"
4. Run the Spike
Execute the experiment. This may involve:
- Writing small test scripts or prototype code in the spike directory
- Making API calls to test endpoint behavior
- Cloning a target repo and reading/testing code
- Testing configurations or library behavior
- Any other hands-on investigation
Keep the code minimal and focused. This is a throwaway experiment, not production code.
5. Record Results
Update the spike's README.md Results and Conclusion sections with:
- What happened? What did we observe?
- Does this validate or invalidate the assumption?
- Include any relevant output, error messages, or data
6. Update Planning Documents
- assumptions.md: Update the relevant assumption's confidence score and notes based on spike results
- research.md: Add a brief summary of the spike and its findings under a new section
- session.md: Use the CLI to record the spike:
python3 bin/planning update-session \ --project <project-slug> \ --idea <idea-slug> \ --add-decision "Spike confirmed: <finding>" \ --add-next-step "<what to do next based on results>"
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 · 76 lines · 35 tokens per session scan A 9739d75fefd9
spike is a skill published in the GitHub repository nickmisasi/planner (5 stars, last pushed 4mo ago), licensed MIT. It adds 35 tokens to every session and 686 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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