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 skills add GGbond-bo/MemOmics-Agent --skill spikegit clone --depth 1 https://github.com/GGbond-bo/MemOmics-AgentWrote 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/ggbond-bo/memomics-agent/spike)<a href="https://agentmods.dev/skills/ggbond-bo/memomics-agent/spike"><img src="https://agentmods.dev/badge/skills/ggbond-bo/memomics-agent/spike/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/ggbond-bo/memomics-agent/spike"><img src="https://agentmods.dev/badge/skills/ggbond-bo/memomics-agent/spike.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00013 | $0.02150 |
| Opus 5 | $0.00006 | $0.01075 |
| Sonnet 5 | $0.00003 | $0.00430 |
| Haiku 4.5 | $0.00001 | $0.00215 |
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 5d 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.
This is a copy
95% identical to spike — 4 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 198 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Spike
Use this skill when the user wants to feel out an idea before committing to a real build — validating feasibility, comparing approaches, or surfacing unknowns that no amount of research will answer. Spikes are disposable by design. Throw them away once they've paid their debt.
Load this when the user says things like "let me try this", "I want to see if X works", "spike this out", "before I commit to Y", "quick prototype of Z", "is this even possible?", or "compare A vs B".
When NOT to use this
- The answer is knowable from docs or reading code — just do research, don't build
- The work is production path — use the
planskill instead - The idea is already validated — jump straight to implementation
If the user has the full GSD system installed
If gsd-spike shows up as a sibling skill (installed via npx get-shit-done-cc --hermes), prefer gsd-spike when the user wants the full GSD workflow: persistent .planning/spikes/ state, MANIFEST tracking across sessions, Given/When/Then verdict format, and commit patterns that integrate with the rest of GSD. This skill is the lightweight standalone version for users who don't have (or don't want) the full system.
Core method
Regardless of scale, every spike follows this loop:
decompose → research → build → verdict
↑__________________________________________↓
iterate on findings
1. Decompose
Break the user's idea into 2-5 independent feasibility questions. Each question is one spike. Present them as a table with Given/When/Then framing:
| # | Spike | Validates (Given/When/Then) | Risk |
|---|---|---|---|
| 001 | websocket-streaming | Given a WS connection, when LLM streams tokens, then client receives chunks < 100ms | High |
| 002a | pdf-parse-pdfjs | Given a multi-page PDF, when parsed with pdfjs, then structured text is extractable | Medium |
| 002b | pdf-parse-camelot | Given a multi-page PDF, when parsed with camelot, then structured text is extractable | Medium |
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.
- 5d ago First seen · 198 lines · 13 tokens per session scan A 891bc0a6fbb7
spike is a skill published in the GitHub repository GGbond-bo/MemOmics-Agent (19 stars, last pushed 6d ago), licensed MIT. It adds 13 tokens to every session and 2,150 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 95% identical to spike, differing in 4 lines, and is treated as a copy.
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