Specify a webhook-driven task for OpenClaw
Describe event inputs, validation, deduplication, and intended actions before integration work.
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Use when designing, building, reviewing, testing, or improving agents, agentic workflows, agent skills, MCP servers, tool interfaces, subagent systems, or agent-development methodology
--- name: best-practices-for-agentic-development-a3883c92f61f description: Use when designing, building, reviewing, testing, or improving agents, agentic workflows, agent skills, MCP servers, tool interfaces, subagent systems, or agent-development methodology metadata: last_updated: "2026-08-18" --- # Best Practices for Agentic Development Use this as the master routing skill for agentic-development work. Load the reference file that matches the task before making design or implementation decisions. Core principle: Agentic systems are engineered through behavior, context, tools, evals, and operational guardrails. Do not solve every problem with a larger prompt. ## Route First Pick the relevant reference: | Task | Read | | --- | --- | | Creating, editing, packaging, auditing, or testing skills | `references/skill-development.md` | | Designing an agent product, tool-using assistant, memory layer, eval loop, or agent architecture | `references/general-agent-development.md` | | Building multi-step software-development workflows with planning, subagents, verification, reviews, worktrees, and delivery gates | `references/agentic-development.md` | | Designing or implementing MCP servers, MCP tools, tool schemas, resources, prompts, or context-efficient MCP workflows | `references/mcp-development.md` | If more than one applies, read the most specific file first, then read others only for missing concerns. ## Universal Practices Apply these across all agentic-development work: 1. **State the behavior.** Define what the agent should do in observable terms. 2. **Choose the right enforcement surface.** Use skills for judgment, tools/scripts for deterministic checks, hooks for runtime gates, and evals for behavioral confidence. 3. **Use progressive disclosure.** Keep always-loaded context small; load details on demand. 4. **Prefer gates over rules.** A gate blocks progress until objective evidence exists. 5. **Test behavior under pressure.** Normal prompts do not prove adherence. 6. **Capture rationalizations.** Convert observed excuses into red flags and counters. 7. **Verify before claiming.** Completion claims need fresh evidence. 8. **Design for harness reality.** Detect available tools, sandbox limits, worktree state, subagents, hooks, and native capabilities before acting. 9. **Match guidance form to the failure shape.** Prohibition, positive recipe, structural required field, or condition. Prohibition is not a universal fix. See skill-development.md. ## Enforcement Surface Decision | Need | Use | | --- | --- | | Reusable judgment, workflow, or pattern | Skill | | Large reference or examples | Markdown reference file | | Repeated deterministic operation | Script or CLI | | Runtime stop/continue/approval decision | Hook or wrapper | | Agent-visible external capability | MCP tool | | Large API or data processing without context bloat | MCP-exec-style fetch/filter/summarize workflow | | Confidence that behavior holds | Eval harness with transcripts and assertions | | Durable behavioral rule that must survive across turns | Re-inject into system prompt every turn (mutable rules file), not a one-time note or memory — see general-agent-development.md | ## Red Flags Stop and re-evaluate when you think: - "This is just prompt wording." - "The agent will probably infer the right thing." - "We can test later." - "A bigger instruction block will fix it." - "The tool schema can be verbose because context is large." - "The subagent can just read the whole conversation." - "The happy path worked once." - "A prohibition list will fix this." These are signs you need routing, gates, sharper context, or evals. ## Completion Criteria Before considering agentic-development work complete: - Relevant reference file has been applied. - Behavior is stated in observable terms. - Triggering/discovery path is clear. - Context-loading strategy is explicit. - Failure modes and rationalizations are addressed. - Deterministic checks are automated where possible. - Verification or eval evidence exists for behavior-changing work.--- name: best-practices-for-agentic-development-a3883c92f61f description: Use when designing, building, reviewing, testing, or improving agents, agentic workflows, agent skills, MCP servers, tool interfaces, subagent systems, or agent-development methodology metadata: last_updated: "2026-08-18" --- # Best Practices for Agentic Development Use this as the master routing skill for agentic-development work. Load the reference file that matches the task before making design or implementation decisions. Core principle: Agentic systems are engineered through behavior, context, tools, evals, and operational guardrails. Do not solve every problem with a larger prompt. ## Route First Pick the relevant reference: | Task | Read | | --- | --- | | Creating, editing, packaging, auditing, or testing skills | `references/skill-development.md` | | Designing an agent product, tool-using assistant, memory layer, eval loop, or agent architecture | `references/general-agent-development.md` | | Building multi-step software-development workflows with planning, subagents, verification, reviews, worktrees, and delivery gates | `references/agentic-development.md` | | Designing or implementing MCP servers, MCP tools, tool schemas, resources, prompts, or context-efficient MCP workflows | `references/mcp-development.md` | If more than one applies, read the most specific file first, then read others only for missing concerns. ## Universal Practices Apply these across all agentic-development work: 1. **State the behavior.** Define what the agent should do in observable terms. 2. **Choose the right enforcement surface.** Use skills for judgment, tools/scripts for deterministic checks, hooks for runtime gates, and evals for behavioral confidence. 3. **Use progressive disclosure.** Keep always-loaded context small; load details on demand. 4. **Prefer gates over rules.** A gate blocks progress until objective evidence exists. 5. **Test behavior under pressure.** Normal prompts do not prove adherence. 6. **Capture rationalizations.** Convert observed excuses into red flags and counters. 7. **Verify before claiming.** Completion claims need fresh evidence. 8. **Design for harness reality.** Detect available tools, sandbox limits, worktree state, subagents, hooks, and native capabilities before acting. 9. **Match guidance form to the failure shape.** Prohibition, positive recipe, structural required field, or condition. Prohibition is not a universal fix. See skill-development.md. ## Enforcement Surface Decision | Need | Use | | --- | --- | | Reusable judgment, workflow, or pattern | Skill | | Large reference or examples | Markdown reference file | | Repeated deterministic operation | Script or CLI | | Runtime stop/continue/approval decision | Hook or wrapper | | Agent-visible external capability | MCP tool | | Large API or data processing without context bloat | MCP-exec-style fetch/filter/summarize workflow | | Confidence that behavior holds | Eval harness with transcripts and assertions | | Durable behavioral rule that must survive across turns | Re-inject into system prompt every turn (mutable rules file), not a one-time note or memory — see general-agent-development.md | ## Red Flags Stop and re-evaluate when you think: - "This is just prompt wording." - "The agent will probably infer the right thing." - "We can test later." - "A bigger instruction block will fix it." - "The tool schema can be verbose because context is large." - "The subagent can just read the whole conversation." - "The happy path worked once." - "A prohibition list will fix this." These are signs you need routing, gates, sharper context, or evals. ## Completion Criteria Before considering agentic-development work complete: - Relevant reference file has been applied. - Behavior is stated in observable terms. - Triggering/discovery path is clear. - Context-loading strategy is explicit. - Failure modes and rationalizations are addressed. - Deterministic checks are automated where possible. - Verification or eval evidence exists for behavior-changing work.
Imported from the listed AgentSkill.sh category. Complete supplied package files and notices are retained. Required external tools and credentials are not installed. No bundled code was executed during import. Individual agent task behavior has not been tested.