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 berserkdisruptors/contextual-commits --skill recallgit clone --depth 1 https://github.com/berserkdisruptors/contextual-commitsWrote 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/berserkdisruptors/contextual-commits/recall)<a href="https://agentmods.dev/skills/berserkdisruptors/contextual-commits/recall"><img src="https://agentmods.dev/badge/skills/berserkdisruptors/contextual-commits/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.
<a href="https://agentmods.dev/skills/berserkdisruptors/contextual-commits/recall"><img src="https://agentmods.dev/badge/skills/berserkdisruptors/contextual-commits/recall.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 | $0.00043 | $0.02644 |
| Opus 5.5 | $0.00017 | $0.01058 |
| Sonnet 5.5 | $0.00009 | $0.00529 |
| Haiku 4.5 | $0.00004 | $0.00264 |
Grade A, and why
recall scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 322 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Context Recall
Reconstruct the development story from contextual commit history and present it as a natural briefing.
Argument Detection
Check how recall was invoked:
- No arguments — run the default mode (full branch/session briefing below).
- Bare word (e.g.
recall auth) — treat as a scope query. Jump to Scope Query. word(word)pattern (e.g.recall rejected(auth)) — treat as an action+scope query. Jump to Action+Scope Query.
Default Mode (no arguments)
Step 1: Detect Branch State
Determine the working state:
CURRENT_BRANCH=$(git branch --show-current)
DEFAULT_BRANCH=$(git symbolic-ref refs/remotes/origin/HEAD 2>/dev/null | sed 's@^refs/remotes/origin/@@' || echo "main")
# Find the actual parent branch, not just the repo default.
# Try upstream tracking branch first (fast path).
BASE_BRANCH=$(git rev-parse --abbrev-ref @{upstream} 2>/dev/null | sed 's|^origin/||')
# If no upstream, find the nearest local branch by commit distance.
if [ -z "$BASE_BRANCH" ]; then
BASE_BRANCH=$(git for-each-ref --format='%(refname:short)' refs/heads/ | while read branch; do
[ "$branch" = "$CURRENT_BRANCH" ] && continue
echo "$(git log --oneline "$branch..$CURRENT_BRANCH" 2>/dev/null | wc -l | tr -d ' ') $branch"
done | sort -n | head -1 | awk '{print $2}')
fi
# Final fallback to default branch.
BASE_BRANCH=${BASE_BRANCH:-$DEFAULT_BRANCH}
UNSTAGED=$(git diff --stat)
STAGED=$(git diff --cached --stat)
BRANCH_COMMITS=$(git log ${BASE_BRANCH}..HEAD --oneline 2>/dev/null | wc -l | tr -d ' ')
DEFAULT_BRANCH identifies the repository's primary branch (for scenario C/D detection). BASE_BRANCH identifies the closest ancestor branch — which may differ when feature branches are created from non-default branches (e.g., a feature branched from develop). All branch-relative queries use BASE_BRANCH.
Step 2: Gather Raw Material
Scenario A — On a feature branch with commits
This is the richest scenario. Gather:
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.
- 1mo ago First seen · 322 lines · 43 tokens per session scan A 4a877474e6c8
recall is a skill published in the GitHub repository berserkdisruptors/contextual-commits (154 stars, last pushed 5mo ago), licensed MIT. It adds 43 tokens to every session and 2,644 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.
Other skills, from other repositories
release-announcement
Write a release announcement — changelog, blog post, in-app note, or social post — that leads with user impact, names the audience, and includes upgrade/migration steps without filler.
github-pr-workflow
Prepare a GitHub pull request from a feature branch — branch hygiene, commit shape, title/body, verification notes, screenshots for UI work, and replies to review comments.
wiki-ingest
Use when an operation issue asks to ingest a captured raw/ source into the LLM Wiki, or the user says "ingest ". Create durable source, entity, concept, synthesis, index, and log pages; use paperclip-distill for Paperclip bundles.
wiki-lint
Use when an LLM Wiki operation issue is a lint or health check. Audit for contradictions, orphans, weak provenance, broken links, missing concept pages, and index/log drift; return triage findings without auto-fixing.
para-memory-files
Use a file-based PARA memory system to store, retrieve, and organize durable knowledge across sessions. Trigger on saving facts, daily notes, entity records, weekly synthesis, recall, tacit user patterns, or plan memory.
context-engine
Loads and manages company context for all C-suite advisor skills. Reads /.claude/company-context.md, detects stale context (older than 90 days), enriches context during conversations, and enforces privacy/anonymization rules before external API calls. Use when starting any C-suite advisor session, when context looks…