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 Sapientropic/AIppocampus --skill aippocampus-uxgit clone --depth 1 https://github.com/Sapientropic/AIppocampusWrote 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/sapientropic/aippocampus/aippocampus-ux)<a href="https://agentmods.dev/skills/sapientropic/aippocampus/aippocampus-ux"><img src="https://agentmods.dev/badge/skills/sapientropic/aippocampus/aippocampus-ux/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/sapientropic/aippocampus/aippocampus-ux"><img src="https://agentmods.dev/badge/skills/sapientropic/aippocampus/aippocampus-ux.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 | $0.00096 | $0.01215 |
| Opus 5 | $0.00048 | $0.00607 |
| Sonnet 5 | $0.00019 | $0.00243 |
| Haiku 4.5 | $0.00010 | $0.00121 |
Grade A, and why
aippocampus-ux 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 10d 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 — 118 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AIppocampus UX
Overview
Use this skill to make AIppocampus usable by a foreground agent on behalf of a human. The bar is not generic visual polish: AIppocampus UX should be clear like Linear, fast like Raycast, and integrable/recoverable like Stripe while preserving source-backed boundaries.
This is a product/agent-use skill, not a design-director critique. Optimize for the next agent being able to decide, pull the right source route, act, recover, and leave feedback without reading audit-scale internals.
For broad reviews, issue triage, or new foreground contracts, read
references/agent-facing-ux-charter.md. For a tiny copy, CLI, or card fix, use
the workflow below directly.
Workflow
-
Reopen the task source.
Use the current issue, PR, comments, docs, code, or CLI output before judging the surface. If older AIppocampus context may affect the work, use the normal AIppocampus orientation/recall route first. Treat route packets as navigation until source is opened.
-
Classify the surface.
Pick one primary class before recommending fields or tests:
foreground_agent_action: compact route, action card, hook hint, MCP/CLI result, or recovery card used by an active agent.operator_debug: diagnostics, red lines, policy ledgers, run metadata, or private local detail for maintainers.public_demo: public-safe docs, examples, screenshots, or first-run proof.source_court: deepen/source-open output used for exact, public, stale, sensitive, disputed, or high-risk claims.benchmark_report: evaluation, readiness, or evidence reports.setup_onboarding: install, update, hook, provider, sync, or readiness flows.
-
Map the agent journey.
Use the Access / Context / Tools / Orchestration map:
- Access: can the agent tell whether AIppocampus is installed, current, and callable in this host?
- Context: does the agent receive a small useful continuity lead, not audit-scale JSON?
- Tools: are recall, deepen, explain, feedback, setup, and recovery paths discoverable with clear scopes?
- Orchestration: can a fresh agent complete recall -> deepen/source -> act -> feedback without inventing broad manual search first?
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 10d ago First seen · 118 lines · 96 tokens per session scan A 16e2f5be09c7
aippocampus-ux is a skill published in the GitHub repository Sapientropic/AIppocampus (5 stars, last pushed 22d ago), licensed Apache-2.0. It adds 96 tokens to every session and 1,215 once invoked, about $0.0005 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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