A collection of reusable skills for AI coding agents, mainly for Claude Code.
npx skills add https://github.com/trancong12102/agentskills --skill deps-devInstala esta habilidad con la CLI y comienza a usar el flujo de trabajo SKILL.md en tu espacio de trabajo.
Reusable skills and agents for AI coding agents, primarily Claude Code.
Most Claude Code agent frameworks (11–24 agents, 9+ hooks) add complexity to compensate for weaker models. With Opus 4.6, that complexity burns tokens without improving output. ora ships exactly two research agents:
Both isolate search context from the main conversation — broad queries never pollute your main window. The plugin has no hooks and no planning/verification/execution agents. Planning and verification happen inline in the main agent, shaped by behavioral rules in your CLAUDE.md (see Configuration below).
# Plugin (agents)
/plugin marketplace add trancong12102/agentskills
/plugin install ora@agentskills
# Skills (optional, standalone)
bunx skills add trancong12102/agentskills -g -y -a claude-code
# Other plugins
/plugin install sound-notify@agentskills
| Skill | Credential | How to get |
|---|---|---|
godgrep |
MORPH_API_KEY env var |
Sign up at morphllm.com (codebase-search) |
godfetch |
CONTEXT7_API_KEY env var |
Sign up at context7.com (library docs) |
godfetch |
MORPH_API_KEY env var |
Sign up at morphllm.com (GitHub code search) |
oracle |
Codex CLI auth | Run codex login after installing Codex CLI |
Add to ~/.codex/config.toml:
[profiles.oracle]
model = "gpt-5.4"
model_reasoning_effort = "xhigh"
approval_policy = "never"
sandbox_mode = "read-only"
| Agent | Model | Role |
|---|---|---|
ora:Ariadne |
Sonnet | Codebase exploration — traces flows, finds implementations, maps architecture. |
ora:Clio |
Sonnet | External research — fetches docs, searches GitHub repos, checks versions. |
ora is just two agents — workflow behavior lives in your ~/.claude/CLAUDE.md. Recommended setup:
<investigate_before_responding>
Do not respond to tech task without loading matching skill or spawning ora:Clio research first. Cost near zero; stale knowledge break implementations. Skip only when task clearly unrelated to any skill.
Never speculate on code not opened. User reference specific file → read file first. Ground all claims in investigated state.
</investigate_before_responding>
<subagent_routing>
Do not use built-in Explore or general-purpose agent — use ora:Ariadne (local codebase) and ora:Clio (external sources). general-purpose escape hatch only when no ora agent fits.
Do not serialize independent subagent work. Fan out parallel: spawn multiple subagents in single turn when work covers independent items/files.
Do not respawn agents. Follow-up on agent already spawned this session → SendMessage with returned agentId. Fresh spawn lose cached context and repeat tool calls. New Agent call only when topic genuinely different.
</subagent_routing>
<plan_before_implementing>
Do not implement without calling EnterPlanMode tool first when task ambiguous, spans multiple subsystems, or acceptance criteria unclear. Skip plan mode for clearly-scoped changes: single-file bug fix with obvious fix site, mechanical rename/refactor, config/typo fix.
</plan_before_implementing>
<think_before_coding>
Do not start implementing without stating assumptions and flagging tradeoffs. Multiple reasonable interpretations → present them, do not pick silent. Simpler approach exist than asked → say so, push back. Unclear enough to block correct execution → stop and ask, do not guess.
</think_before_coding>
<goal_driven_execution>
Do not accept vague goals. Translate each task into verifiable success criterion before implementing ("add validation" → "write tests for invalid inputs, then make them pass"). Do not mark task complete until success criterion met — read actual code, run actual check, do not trust own summary.
</goal_driven_execution>
<ask_user_question_tool>
Do not ask user via plain response. Use AskUserQuestion tool — load via `ToolSearch` with `select:AskUserQuestion`.
</ask_user_question_tool>
think_before_coding and goal_driven_execution are adapted from forrestchang/andrej-karpathy-skills.
MIT — Cong Tran