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/stepzerolab/research-git/rgit-recallnpx skills add StepzeroLab/research-git --skill rgit-recallgit clone --depth 1 https://github.com/StepzeroLab/research-gitWhat 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 | $0.00045 | $0.00953 |
| Opus 5 | $0.00023 | $0.00477 |
| Sonnet 5 | $0.00009 | $0.00191 |
| Haiku 4.5 | $0.00005 | $0.00095 |
Grade A, and why
rgit-recall scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 59 lines — stays where its author put it; the contents beside it link to each section on GitHub.
rgit-recall
Drives the recall → compose → regenerate half of the research-git loop. The stored capsule is a spec; the regenerator rebuilds it onto today's code.
Prerequisites: the repo is rgit init-ed and the research-git MCP server is connected (it exposes recall and compose).
Locating the agent definitions. On Claude Code the plugin runtime resolves agent paths for you. On other CLIs (Codex, Gemini, opencode) this skill is symlinked into ~/.agents/skills/rgit-recall, so resolve the plugin root once and reference the agent from there:
SKILL_REAL=$(realpath ~/.agents/skills/rgit-recall 2>/dev/null || readlink -f ~/.agents/skills/rgit-recall)
PLUGIN_ROOT=$(dirname "$(dirname "$SKILL_REAL")") # the bundled _plugin/ directory
The agents/capsule-regenerator.md reference below lives at $PLUGIN_ROOT/agents/capsule-regenerator.md.
Process
1. Recall the capsule(s)
Take the user's natural-language ask and call the MCP tool recall(query). It returns matches, each with its depends_on subgraph. Show the user a short list (name + intent) and confirm which feature(s) to bring back. Default to the top match if unambiguous. If nothing matches, tell the user and stop (suggest list_features to browse).
2. Resolve the full feature set
Include each chosen capsule plus its depends_on dependencies (a feature often needs its prerequisites). Collect the final list of feature_ids.
3. Compose the regeneration brief (against current code)
Call the MCP tool compose(feature_ids). It returns, per feature: intent, knobs, data_assumptions, resurrection_guide, the reference code_slices, the live current_source of each touched symbol, and any conflicts (symbols touched by more than one chosen feature).
4. Dispatch the capsule-regenerator subagent (on subscription)
Dispatch a subagent using the capsule-regenerator agent definition (agents/capsule-regenerator.md). Pass the full brief verbatim plus repo_root. The subagent edits the working tree to re-implement the feature(s) onto today's code, resolves conflicts, sanity-checks syntax, and returns an applied report with provenance (clean vs adapted) per feature.
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.
- 2d ago First seen · 59 lines · 45 tokens per session scan A f39d6e88e5a6
rgit-recall is a skill published in the GitHub repository StepzeroLab/research-git (42 stars, last pushed 27d ago), licensed MIT. It adds 45 tokens to every session and 953 once invoked, about $0.0002 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.
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