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 janbjorge/rekal --skill rekal-initgit clone --depth 1 https://github.com/janbjorge/rekalWrote 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/janbjorge/rekal/rekal-init)<a href="https://agentmods.dev/skills/janbjorge/rekal/rekal-init"><img src="https://agentmods.dev/badge/skills/janbjorge/rekal/rekal-init.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Privilege Escalation · line 334 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- medium Excessive Agency · line 350 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00083 | $0.03797 |
| Opus 5 | $0.00042 | $0.01899 |
| Sonnet 5 | $0.00017 | $0.00759 |
| Haiku 4.5 | $0.00008 | $0.00380 |
Grade A, and why
rekal-init 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 8d 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 — 357 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Bootstrap rekal memory from a codebase. Goal: a fresh agent in a new session has enough context to work effectively without the user repeating themselves.
Requirements
- Execute ALL steps including Tier 4 (source code scanning). Do NOT stop after reading docs and config.
- Run every Grep command in Tier 4. Each grep with results → at least 1 memory.
- Store at least 1 memory per source module discovered in the codebase.
- Read high-signal docs first (CLAUDE.md, AGENTS.md). They reveal what else to scan.
- Follow breadcrumbs. If docs reference other files or dirs, read those too.
- Run the self-check in Step 7 before finishing.
- On a fresh DB, skip dedup searches. Nothing to dedup against. Store directly.
Common failure: agent reads docs + config, stores ~20 memories, skips source code scanning entirely. Do not do this.
Step 0: Pre-flight
rekal health
Report current state. If the project already has memories, warn and wait for confirmation. For a fresh database, continue automatically.
Step 1: Identify the project
Determine the project name from the working directory, git remote, or config files. Prefer short, lowercase names: rekal, backend, myapp. Pass it as project="<name>" on every memory_store call below.
Step 2: Scan for knowledge sources
Search for these files in priority order. Read every file that exists. Skip what's missing.
Tier 1: High-signal project docs (read fully, read FIRST)
CLAUDE.md, AGENTS.md, .claude/CLAUDE.md
README.md, README.rst, README.txt
CONTRIBUTING.md, ARCHITECTURE.md, DESIGN.md, ADR/*.md
docs/architecture.md, docs/design.md, docs/conventions.md
Read these BEFORE other tiers. They frequently reference:
- Specific directories or modules to pay attention to
- Conventions not captured in linter configs
- Domain-specific terminology and concepts
- Workflows, procedures, and tool preferences
- Other documentation files worth reading
Follow the breadcrumbs. If CLAUDE.md says "read AGENTS.md before doing anything" or references docs/api-guide.md, read those files too. If AGENTS.md describes a specific architecture, that's a 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.
- 8d ago First seen · 357 lines · 83 tokens per session scan A ea88e8ae6efc
rekal-init is a skill published in the GitHub repository janbjorge/rekal (53 stars, last pushed 13d ago), licensed MIT. It adds 83 tokens to every session and 3,797 once invoked, about $0.0004 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 2026-08-30.
Other skills, from other repositories
vault-for-llm
Connect OpenClaw to Vault Agent Memory as a local-first governed project memory layer. Search first, then bounded-read cited source ranges; propose new memories as candidates instead of writing directly into active memory.
hmem-write
Hmem write protocol — picks prefix (L/E/D/P/N/R/I/H…), tree location, and tags, and detects duplicates before persisting. Use before any writememory or appendmemory call (skipping it creates duplicates and misplaced entries), or when the user says 'remember this', 'save this', 'log this', or invokes /hmem-write.
hmem-config
View and change hmem memory settings, hooks, sync, and checkpoints. Use on /hmem-config, or when the user asks why context is huge, how to change auto-save, how often checkpoints fire, or how to set up sync.
hmem-read
Load long-term memory from hmem via readmemory or loadproject. Use when starting fresh with no L1 summaries, after /compact, when the user asks 'what do you remember', 'continue where we left off', 'was war der letzte Stand', or about a project/topic visible in L1 summaries. Covers search, prefix filter, findrelated…
hmem-curate
Curate an .hmem file (your own or foreign) — mark obsolete/irrelevant, fix titles, consolidate duplicates, repair broken links. Requires the hmem-curate MCP server (skill prompts the user to enable it on entry). Use whenever the user says 'aufräumen', 'memory aufräumen', 'Speicher aufräumen', 'hmem aufräumen', 'clean…
hmem-migrate-o
Migrate O-entries to the v5.3+ project-bound 5-level structure (each O00XX bound to its P00XX). Use on 'migrate O-entries', when hmem-update flags a structure migration, or when you notice O-entries still in the old flat L2→L4→L5 format.