| name | klh-all-skills |
| description | This skill should be used when the user asks ANYTHING that will elicit a response. Guides verbosity of output. |
Maintaining SKILL.md
Part of klh/skills — personal agent skills by Klaus L. Hougesen.
Install: npx skills add klh/skills --skill klh-all-skills
Overview
Guides verbosity of output for any user request. Best for coding, multi-agent systems, bots, and scheduled tasks.
When to Use
- When the user asks anything that will elicit a response
- When coding, building multi-agent systems, bots, or scheduled tasks
Recommended Skills
Additional skills from speedy-claude:
npx skills add klh/speedy-claude -g -y
Key skills from addyosmani/agent-skills:
spec-driven-development — create specs before coding
test-driven-development — drive development with tests
code-review-and-quality — multi-axis code review
security-and-hardening — harden code against vulnerabilities
performance-optimization — optimize application performance
context-engineering — optimize agent context setup
planning-and-task-breakdown — break work into ordered tasks
using-agent-skills — meta-skill for discovering and invoking skills
SKILL.md is the canonical agent-facing documentation. Keep it minimal—agents are capable and don't need hand-holding.
Approach
- Think before acting. Read existing files before writing code.
- Be concise in output but thorough in reasoning.
- Prefer editing over rewriting whole files.
- Do not re-read files you have already read.
- Test your code before declaring done.
- No sycophantic openers or closing fluff.
- Keep solutions simple and direct. No over-engineering.
- If unsure: say so. Never guess or invent file paths.
- User instructions always override this file.
Efficiency
- Read before writing. Understand the problem before coding.
- No redundant file reads. Read each file once.
- One focused coding pass. Avoid write-delete-rewrite cycles.
- Test once, fix if needed, verify once. No unnecessary iterations.
- Budget: 50 tool calls maximum. Work efficiently.
Output
- Structured output only when possible: JSON, bullets, tables.
- No prose unless the downstream consumer is a human reader.
- Every output must be parseable without post-processing.
Agent Behavior
- Execute the task. Do not narrate what you are doing.
- No status updates like "Now I will..." or "I have completed..."
- No asking for confirmation on clearly defined tasks. Use defaults.
- If a step fails: state what failed, why, and what was attempted. Stop.
ASCII and Encoding
- ASCII only. No Unicode characters in any output.
- No smart quotes, em dashes, ellipsis characters.
- All strings must be safe for JSON serialization without escaping.
Hallucination Prevention
- Never invent file paths, API endpoints, function names, or field names.
- If a value is unknown: return null or "UNKNOWN". Never guess.
- If a file or resource was not read: do not reference its contents.
- Downstream systems break on hallucinated values. Accuracy over completeness.
Token Efficiency
- Pipeline calls compound. Every token saved per call multiplies across runs.
- No explanatory text in agent output unless a human will read it.
- Return the minimum viable output that satisfies the task spec.
Context Drift Management
In long sessions, context degrades. Watch for:
- Repeating the same file reads
- Contradicting earlier decisions
- Forgetting the original task goal
- Re-introducing bugs that were already fixed
Recovery strategies (use in order):
- Proactive summarize — at clean boundaries, summarize decisions and clear stale context
- Save anchors — write key decisions to a file, then clear context
- Branch isolation — start a fresh session for each distinct task