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/drafthq/draft/learnnpx skills add drafthq/draft --skill learngit clone --depth 1 https://github.com/drafthq/draftWhat 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 | $0.00042 | $0.05465 |
| Opus 5 | $0.00021 | $0.02733 |
| Sonnet 5 | $0.00008 | $0.01093 |
| Haiku 4.5 | $0.00004 | $0.00547 |
Grade A, and why
learn 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 — 513 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Learn — Pattern Discovery & Guardrails Update
Scan the codebase to discover recurring coding patterns and update draft/guardrails.md with learned conventions and anti-patterns. This improves future quality command accuracy by reducing false positives and catching known-bad patterns.
MANDATORY GRAPH LOOKUP (read before pattern scanning)
First resolve the bundled helpers:
# Locate Draft's bundled helpers (cwd is the user's project; ${CLAUDE_PLUGIN_ROOT}
# is not exported into skill Bash). See core/shared/tool-resolver.md.
DRAFT_TOOLS="${DRAFT_PLUGIN_ROOT:-$(cat ~/.cache/draft/plugin-root 2>/dev/null)}/scripts/tools"
[ -d "$DRAFT_TOOLS" ] || DRAFT_TOOLS="$(ls -d ~/.claude/plugins/cache/*/draft/*/scripts/tools 2>/dev/null | sort -V | tail -1)"
[ -d "$DRAFT_TOOLS" ] || DRAFT_TOOLS="$(ls -d ~/.claude/plugins/marketplaces/*draft*/scripts/tools 2>/dev/null | tail -1)"
[ -d "$DRAFT_TOOLS" ] || DRAFT_TOOLS="$PWD/scripts/tools"
When draft/graph/schema.yaml exists, this skill must follow the graph-first lookup contract in core/shared/graph-query.md §Mandatory Lookup Contract. Use the graph to:
- Enumerate a module's symbols/files via
"$DRAFT_TOOLS/graph-callers.sh"/"$DRAFT_TOOLS/graph-impact.sh"and"$DRAFT_TOOLS/graph-arch.sh" --repo .(preferred overfind). - Prioritize hotspots via
"$DRAFT_TOOLS/hotspot-rank.sh" --repo .— patterns in high-fanIn files are more impactful when learned. - For TS/Python/Go/C/C++, use
*-index.jsonlto identify class/function definitions rather than re-discovering them via regex.
Filesystem find for source discovery (Step 2.1) is permitted as a complement to the graph for languages not covered by indexes (e.g. Ruby, Java without ctags). Record the rationale in the Graph Usage Report.
Red Flags - STOP if you're
See shared red flags — applies to all code-touching skills.
Skill-specific:
- Writing to guardrails.md without reading the codebase first
- Learning a pattern from fewer than 3 occurrences
- Auto-promoting patterns to Hard Guardrails (requires human approval)
- Overwriting human-curated Hard Guardrails with learned patterns
- Learning patterns that contradict
tech-stack.md ## Accepted Patterns - Removing existing learned entries (only update or add)
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 First seen · 513 lines · 42 tokens per session scan A a088521ca6ef
learn is a skill published in the GitHub repository drafthq/draft (40 stars, last pushed 13d ago), licensed MIT. It adds 42 tokens to every session and 5,465 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.
Other skills, from other repositories
memorix-memory
Use when prior workspace context, past decisions, solved bugs, handoff state, or durable project knowledge would help a coding task.
memorix
Use when Claude Code needs Memorix shared memory, reasoning, Git Memory, mini-skills, session handoff, orchestration coordination, or integration troubleshooting.
memorix-mini-skills
Use when durable project knowledge, gotchas, workflows, or repeated fixes should become reusable agent guidance instead of ordinary memory.
memorix-orchestrate
Use when a main agent needs Memorix to coordinate explicit subagent work through tasks, handoffs, messages, file locks, or the orchestrate CLI.
memorix-reasoning
Use when a technical decision, trade-off, rejected alternative, architecture rationale, or design risk should be recorded or recovered.
memorix-troubleshooting
Use when Memorix MCP, setup, project binding, HTTP control plane, hooks, skills, or agent integration is missing, stale, or failing.