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/underpass-ai/kmp/kmp-memorynpx skills add underpass-ai/kmp --skill kmp-memorygit clone --depth 1 https://github.com/underpass-ai/kmpWrote 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/underpass-ai/kmp/kmp-memory)<a href="https://agentmods.dev/skills/underpass-ai/kmp/kmp-memory"><img src="https://agentmods.dev/badge/skills/underpass-ai/kmp/kmp-memory.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 | $0.00124 | $0.07740 |
| Opus 5 | $0.00062 | $0.03870 |
| Sonnet 5 | $0.00025 | $0.01548 |
| Haiku 4.5 | $0.00012 | $0.00774 |
Grade A, and why
kmp-memory 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.
How it starts
The opening of the file, as written. The whole thing — 650 lines — stays where its author put it; the contents beside it link to each section on GitHub.
KMP agent memory
KMP is graph-temporal memory for agents, reachable over MCP as ten memory
tools plus three semantic view tools. It is a kernel, not a model: every
answer is derived from stored evidence by construction. Nothing here
generates prose. If the memory does not support an answer, kmp_ask returns
UNKNOWN — that is a correct result, not a failure to work around.
Invoked, not assumed
KMP is opt-in. This skill governs what happens once something selects it; it does not claim every session. Four things select it:
- the user names KMP or its memory, in any language — "usa kmp", "what does memory say", "check the store";
- a
/kmp:*skill or command runs; - the project's own instructions (
CLAUDE.md,AGENTS.md) opt in; - the MCP initialize instructions report always-on routing, which an operator
turns on deliberately with
kmp-mcp config memory-routing always.
Without one of those, do the work from the material in front of you and make
no KMP call. An unbidden kmp_wake against an empty or unrelated store is not
a free no-op: it spends a round trip and can shape the answer with evidence
nobody asked for.
Everything below is about a route already underway. Temporal precedence, page continuation, do not leave for repository files mid-page — those govern a KMP call in flight. None of them is a reason to start one.
Use this as a router, not a tool glossary
Choose a lane before the first call, then let every result choose the next
move. Do not select kmp_ask once and keep treating the whole task as semantic
when the evidence says it is not.
Once invoked, known work enters through kmp_wake; apply the remaining rows
to the part of the goal the wake packet did not already answer.
| Signal in the user's goal | First move |
|---|---|
| Continue known work or recover its state | kmp_wake |
| Yesterday, since, before/after, a date, what changed, current/latest/recent state, why now, or a release/decision window | kmp_goto, kmp_near, kmp_rewind or kmp_forward |
| A genuinely non-temporal question answerable from stored evidence | kmp_ask |
| One cited ref must support a consequential claim | kmp_inspect |
| A connection between two refs is part of the claim | kmp_trace |
The user asks to see, show, open, or navigate memory — including muéstrame, enséñame, abre or ver |
Finish the retrieval lane, then kmp_view_open and kmp_view_apply_intent |
| A durable decision, constraint or outcome was reached | kmp_write_memory |
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 Changed · +58 lines 993c43360b8c
- yesterday Changed · +22 lines · +5 tokens per session 666719bd39a4
- 4d ago First seen · 570 lines · 119 tokens per session scan A 075c913abb89
kmp-memory is a skill published in the GitHub repository underpass-ai/kmp (0 stars, last pushed today), licensed Apache-2.0. It adds 124 tokens to every session and 7,740 once invoked, about $0.0006 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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