A skill for finding a previously recorded feature and rebuilding it in the current codebase. It coordinates searching, assembling the feature's context, and handing the work to a regeneration agent.

Use it when you want to recall, resurrect, or re-apply a stored feature, including features that depend on other stored features.

A feature written for an older version of a project may need adaptation before it can return. This process treats the saved record as a description of intent and uses current code as the source of truth.

rgit-recall — Skill for Claude Code by StepzeroLab/research-git

Install

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.

Any agent

npx skills add StepzeroLab/research-git --skill rgit-recall

Clone the repo

git clone --depth 1 https://github.com/StepzeroLab/research-git

Made for: Claude Code.

Or install research-git, the plugin that ships this one along with the rest of its 3 skills, 3 agents.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/stepzerolab/research-git/rgit-recall/github.svg)](https://agentmods.dev/skills/stepzerolab/research-git/rgit-recall)

Your own site

<a href="https://agentmods.dev/skills/stepzerolab/research-git/rgit-recall"><img src="https://agentmods.dev/badge/skills/stepzerolab/research-git/rgit-recall/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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/stepzerolab/research-git/rgit-recall"><img src="https://agentmods.dev/badge/skills/stepzerolab/research-git/rgit-recall.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 45 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 953 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits

NVIDIA SkillSpector pass 7 Sept 2026

How audits are shown

Origin original No closer match found in the catalogue.

Token cost

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	$0.00045	$0.00953
Opus 5.5	$0.00018	$0.00381
Sonnet 5.5	$0.00009	$0.00191
Haiku 4.5	$0.00005	$0.00095

Measured 2mo ago against content hash f39d6e88e5a6, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

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 2mo 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.

src/rgit/_plugin/skills/rgit-recall/SKILL.md · 59 lines

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.

Read the full file on GitHub · 59 lines

Changes

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.

2mo ago First seen · 59 lines · 45 tokens per session scan A f39d6e88e5a6

Subscribe to this mod's changes

rgit-recall is a skill published in the GitHub repository StepzeroLab/research-git (44 stars, last pushed 3mo ago), licensed MIT. It adds 45 tokens to every session and 953 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 2026-08-30.

Building agents Memory and context agentic-coding autoresearch claudecode codex

rgit-recall next to 6 skills from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
rgit-recallStepzeroLab/research-git	Skill	44	3mo ago	MIT	A	45	Claude Code
session-flowYeachan-Heo/oh-my-claudecode	Skill	41k	yesterday	MIT	A	32	Claude Code
wikiYeachan-Heo/oh-my-claudecode	Skill	41k	yesterday	MIT	A	19	Claude Code
agentmemory-configrohitg00/agentmemory	Skill	30k	yesterday	Apache-2.0	A	50	Claude Code
agentmemory-hooksrohitg00/agentmemory	Skill	30k	yesterday	Apache-2.0	A	42	Claude Code
agentmemory-agentsrohitg00/agentmemory	Skill	30k	yesterday	Apache-2.0	A	46	Claude Code
handoffrohitg00/agentmemory	Skill	30k	yesterday	Apache-2.0	A	55	Claude Code

rgit-recall

Getting it into your agent

Wrote this? Show the measurements

What it costs to keep this loaded

Grade A, and why

Nothing flagged

How it starts

rgit-recall

Process

1. Recall the capsule(s)

2. Resolve the full feature set

3. Compose the regeneration brief (against current code)

4. Dispatch the capsule-regenerator subagent (on subscription)

What this file has done since we first saw it

rgit-recall compared with skills from other repositories