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 BeppeTemp/cartographer --skill cartographer-kb-creategit clone --depth 1 https://github.com/BeppeTemp/cartographerWrote 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/beppetemp/cartographer/cartographer-kb-create)<a href="https://agentmods.dev/skills/beppetemp/cartographer/cartographer-kb-create"><img src="https://agentmods.dev/badge/skills/beppetemp/cartographer/cartographer-kb-create/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/beppetemp/cartographer/cartographer-kb-create"><img src="https://agentmods.dev/badge/skills/beppetemp/cartographer/cartographer-kb-create.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 | $0.00053 | $0.03585 |
| Opus 5.5 | $0.00021 | $0.01434 |
| Sonnet 5.5 | $0.00011 | $0.00717 |
| Haiku 4.5 | $0.00005 | $0.00359 |
Grade A, and why
cartographer-kb-create 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 yesterday.
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 — 222 lines — stays where its author put it; the contents beside it link to each section on GitHub.
KB Create — Skill
Purpose
Guide an operator through creating a new Knowledge Base (KB) the persistent, GitOps way: a Gitea repo as source of truth, declared in the server's config (ConfigMap), rolled out, then verified and connected. A KB that only exists as an ad-hoc runtime mount on an emptyDir is not durable.
WARNING — data loss risk. A KB mounted on an
emptyDirvolume that is not declared in the Deployment's ConfigMap (kbs:entry +remote:) dies with the pod: on the next reschedule / rollout the directory is recreated empty and every concept written to it is gone. The ConfigMap + Gitea repo declaration is what makes the KB persistent and reconstructible — the server clones it fresh on every pod start (deployment.md §Bootstrapping a KB from a git remote).
Local/native-service topology. On a single machine served by the local service, the equivalent one-liner is
cartographer kb create <name> --remote <url>: it scaffolds the KB and pushes it to the empty repository (or one holding only a forge's initial commit, which is kept: README/LICENSE/.gitignore) that becomes itsorigin(the remote is mandatory there too, D134). A token withrwscope on the KB can write its instructions, templates and skills: there is no setting to turn on. This skill remains the procedure for the GitOps/Kubernetes topology below, where the KB also has to be declared in the server's ConfigMap.
Reference Files
Two tasks have a full procedure of their own. Read only the file that matches what you are doing — not all of them upfront.
| Task | File |
|---|---|
| Put a skill, subagent, hook, MCP descriptor or instructions block into the KB | references/artifacts.md |
Store an encrypted value the KB can resolve (age key, .sops.yaml, Service concept, secret_refs) |
references/secrets.md |
Steps
1. Create the Gitea repo and the per-KB service user
Create an empty repo <nome>.git on Gitea (for the CLI path kb create also accepts a forge's initial README/LICENSE commit). The KB name is the name: field of its kbs:
entry (D53) — set it explicitly; if omitted it falls back to the repo basename. The name is used everywhere downstream: token scopes
(kb:<nome>:rw/kb:<nome>:r), the ?kb=<nome> query param on multi-KB HTTP, and the
<nome>.token/<nome>.age per-KB file conventions below. Choose it accordingly (kebab-case).
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.
- yesterday Changed · +6 lines a06eaea533ed
- 2d ago First seen · 216 lines · 53 tokens per session scan A d43060f00a52
cartographer-kb-create is a skill published in the GitHub repository BeppeTemp/cartographer (45 stars, last pushed today), licensed Apache-2.0. It adds 53 tokens to every session and 3,585 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-10-23.
Other skills, from other repositories
openlore
Query and publish to an OpenLore knowledge repository over SSH using ordinary shell commands. Use when a task needs project documentation, runbooks, shared team knowledge, or a place to publish findings.
openlore-housekeeping
Audit and maintain a shared OpenLore knowledge repository. Use on a schedule or on request to find stale docs, broken links, unreviewed inbox items, and missing skill coverage, then publish an audit report.
lemmalog
Externalize working memory and logical state into the lemmalog Datalog engine (MCP). Use for ANY multi-step task where state should outlive one context window or span agents: long investigations, debugging sessions, audits, multi-agent searches, systematic explorations, planning with many interdependent constraints…
causal-memory
Causal memory for agents — install/setup the causal-memory MCP server, then record decisions/outcomes and recall them before acting. Trigger when the user asks to install or set up causal-memory/agent memory, when causal-memory MCP tools are available and the agent faces a non-trivial decision (architecture, debugging…
prolong
Recover and use durable coding-session history from PRO-LONG's local append-only log. Use on long-running coding tasks, after context compaction or session resume, when reconstructing prior decisions or tool results, or before repeating work that may already have been attempted.
retrospective
Audit whether prior learnings actually fired, then install mechanisms for this run's recurrences. No finding without an install path and a firing test. Triggers: retrospective, reflect, what did we learn, patterns, post-mortem, why does this keep happening.