compile — Skillopedia

Compile — Knowledge Compiler Reads raw artifacts and compiles them into a structured, interlinked markdown wiki. Inspired by Karpathy's LLM Knowledge Bases. What This Skill Does The knowledge flywheel captures signal reactively (via , , ). closes the loop by: 1. Mining unextracted signal from git and (existing) 2. Growing learnings via validation, synthesis, and gap detection (existing) 3. Compiling raw artifacts into interlinked wiki articles (NEW — the core value) 4. Linting the compiled wiki for contradictions, orphans, and gaps (NEW) 5. Defragging stale and duplicate artifacts (existing)…

.agents/learnings/ .agents/patterns/ 2>/dev/null | while read f; do\n count=$(grep -c '^---

Important: agents should read /llm.txt, /llms.txt, or /.well-known/skills.json to discover the public Skillopedia API.

\"$f\")\n [ \"$count\" -gt 2 ] && echo \"STACKED_FRONTMATTER: $f ($count delimiters)\"\ndone\n\n# Bundled multi-learning files: more than one ## Learning heading\ngrep -rl '^## Learning' .agents/learnings/ 2>/dev/null | while read f; do\n count=$(grep -c '^## Learning' \"$f\")\n [ \"$count\" -gt 1 ] && echo \"BUNDLED: $f ($count learnings in one file)\"\ndone\n\n# Duplicated headings within a file\nfor f in .agents/learnings/**/*.md .agents/patterns/**/*.md; do\n [ -f \"$f\" ] || continue\n dupes=$(grep '^## ' \"$f\" | sort | uniq -d)\n [ -n \"$dupes\" ] && echo \"DUPLICATE_HEADING: $f — $dupes\"\ndone\n```\n\n**Report normalization defects** in the defrag output. If any are found, list them with severity:\n- PLACEHOLDER → HIGH (empty knowledge pollutes retrieval)\n- STACKED_FRONTMATTER → MEDIUM (parsing errors, possible data loss)\n- BUNDLED → HIGH (breaks per-learning citation tracking)\n- DUPLICATE_HEADING → LOW (cosmetic, may confuse extraction)\n\n## Step 6 — Report\n\n```bash\nmkdir -p .agents/compile\n```\n\nWrite `.agents/compile/YYYY-MM-DD-report.md`:\n\n```markdown\n# Compile Report — YYYY-MM-DD\n\n## Compilation Summary\n- Articles compiled: N (new: N, updated: N, unchanged: N)\n- Source artifacts processed: N\n- Topics identified: N\n- Backlinks created: N\n\n## Lint Summary\n- Health score: N/100\n- Contradictions: N | Orphans: N | Stale claims: N | Gaps: N\n\n## New Learnings Proposed\n- [title]: [summary] (source: [research file or synthesis])\n\n## Validations\n- Validated: N | Stale: N (list files) | Contradicted: N (list with explanation)\n\n## Knowledge Gaps\n- [topic]: [evidence] → suggested learning: \"[title]\"\n\n## Defrag Summary\n- Orphaned: N | Duplicates: N | Oscillating goals: N\n\n## Recommendations\n1. [Actionable next step]\n```\n\nIf `bd` is available, create issues for knowledge gaps:\n\n```bash\nbd add \"[Knowledge Gap] \u003ctopic>\" --label knowledge --label compile\n```\n","content_type":"text/markdown; charset=utf-8","language":"markdown","size":12115,"content_sha256":"721b190879e484418d4799d168f59ef72777b3b93eb94f955ab6c81aae8a03a1"},{"filename":"scripts/compile.sh","content":"#!/usr/bin/env bash\nset -euo pipefail\n\n# compile.sh — Pluggable LLM compilation engine for .agents/ → .agents/compiled/\n# Usage: AGENTOPS_COMPILE_RUNTIME=ollama scripts/compile.sh [--sources DIR] [--output DIR] [--incremental] [--force] [--lint-only]\n\nSOURCES_DIR=\".agents\"\nOUTPUT_DIR=\".agents/compiled\"\nINCREMENTAL=true\nLINT_ONLY=false\nHASH_FILE=\"\"\nRUNTIME=\"${AGENTOPS_COMPILE_RUNTIME:-}\"\nOLLAMA_MODEL=\"${AGENTOPS_COMPILE_MODEL:-gemma3:27b}\"\nCLAUDE_MODEL=\"${AGENTOPS_COMPILE_CLAUDE_MODEL:-claude-sonnet-4-20250514}\"\nCLAUDE_CLI_MODEL=\"${AGENTOPS_COMPILE_CLAUDE_CLI_MODEL:-}\"\nOLLAMA_API=\"${OLLAMA_HOST:-http://localhost:11434}\"\nBATCH_SIZE=\"${AGENTOPS_COMPILE_BATCH_SIZE:-25}\"\nMAX_BATCHES=\"${AGENTOPS_COMPILE_MAX_BATCHES:-0}\" # 0 = unlimited\nPREFLIGHT_ONLY=false\n\n# --- Argument parsing ---\nwhile [[ $# -gt 0 ]]; do\n case \"$1\" in\n --sources) SOURCES_DIR=\"$2\"; shift 2 ;;\n --output) OUTPUT_DIR=\"$2\"; shift 2 ;;\n --incremental) INCREMENTAL=true; shift ;;\n --force) INCREMENTAL=false; shift ;;\n --lint-only) LINT_ONLY=true; shift ;;\n --full) shift ;; # default mode, accepted for SKILL.md parity\n --batch-size) BATCH_SIZE=\"$2\"; shift 2 ;;\n --max-batches) MAX_BATCHES=\"$2\"; shift 2 ;;\n --preflight) PREFLIGHT_ONLY=true; shift ;;\n *) echo \"Unknown flag: $1\" >&2; exit 1 ;;\n esac\ndone\n\nHASH_FILE=\"$OUTPUT_DIR/.hashes.json\"\nmkdir -p \"$OUTPUT_DIR\"\n\n# --- Utility functions ---\n\ncompute_hash() {\n if command -v md5sum &>/dev/null; then\n md5sum \"$1\" | cut -d' ' -f1\n else\n md5 -q \"$1\"\n fi\n}\n\nload_hashes() {\n if [[ -f \"$HASH_FILE\" ]]; then\n cat \"$HASH_FILE\"\n else\n echo \"{}\"\n fi\n}\n\nget_stored_hash() {\n local file=\"$1\"\n local hashes=\"$2\"\n echo \"$hashes\" | python3 -c \"\nimport sys, json\ndata = json.load(sys.stdin)\nprint(data.get(sys.argv[1], ''))\n\" \"$file\" 2>/dev/null || echo \"\"\n}\n\n# --- LLM call abstraction ---\n\nllm_call() {\n local system_prompt=\"$1\"\n local user_prompt=\"$2\"\n\n case \"$RUNTIME\" in\n ollama)\n local payload\n payload=$(python3 -c \"\nimport json, sys\nprint(json.dumps({\n 'model': '$OLLAMA_MODEL',\n 'messages': [\n {'role': 'system', 'content': sys.argv[1]},\n {'role': 'user', 'content': sys.argv[2]}\n ],\n 'stream': False\n}))\n\" \"$system_prompt\" \"$user_prompt\")\n curl -sf \"$OLLAMA_API/api/chat\" \\\n -H \"Content-Type: application/json\" \\\n -d \"$payload\" | python3 -c \"import sys,json; print(json.load(sys.stdin)['message']['content'])\"\n ;;\n claude)\n local payload\n payload=$(python3 -c \"\nimport json, sys\nprint(json.dumps({\n 'model': '$CLAUDE_MODEL',\n 'max_tokens': 4096,\n 'system': sys.argv[1],\n 'messages': [{'role': 'user', 'content': sys.argv[2]}]\n}))\n\" \"$system_prompt\" \"$user_prompt\")\n curl -sf \"https://api.anthropic.com/v1/messages\" \\\n -H \"Content-Type: application/json\" \\\n -H \"x-api-key: ${ANTHROPIC_API_KEY:?ANTHROPIC_API_KEY required for claude runtime}\" \\\n -H \"anthropic-version: 2023-06-01\" \\\n -d \"$payload\" | python3 -c \"import sys,json; print(json.load(sys.stdin)['content'][0]['text'])\"\n ;;\n claude-cli)\n # Use the locally installed `claude` binary in headless (-p) mode.\n # No API key required; inherits the user's Claude Code auth.\n if ! command -v claude &>/dev/null; then\n echo \"ERROR: claude-cli runtime requested but 'claude' binary not on PATH.\" >&2\n exit 1\n fi\n local combined=\"${system_prompt}\n\n${user_prompt}\"\n if [[ -n \"$CLAUDE_CLI_MODEL\" ]]; then\n printf '%s' \"$combined\" | claude -p --model \"$CLAUDE_CLI_MODEL\" 2>/dev/null\n else\n printf '%s' \"$combined\" | claude -p 2>/dev/null\n fi\n ;;\n openai)\n local payload\n payload=$(python3 -c \"\nimport json, sys\nprint(json.dumps({\n 'model': '${AGENTOPS_COMPILE_OPENAI_MODEL:-gpt-4o}',\n 'messages': [\n {'role': 'system', 'content': sys.argv[1]},\n {'role': 'user', 'content': sys.argv[2]}\n ]\n}))\n\" \"$system_prompt\" \"$user_prompt\")\n curl -sf \"${OPENAI_BASE_URL:-https://api.openai.com}/v1/chat/completions\" \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer ${OPENAI_API_KEY:?OPENAI_API_KEY required for openai runtime}\" \\\n -d \"$payload\" | python3 -c \"import sys,json; print(json.load(sys.stdin)['choices'][0]['message']['content'])\"\n ;;\n *)\n echo \"ERROR: AGENTOPS_COMPILE_RUNTIME must be set to one of: ollama, claude, claude-cli, openai.\" >&2\n echo \"\" >&2\n echo \"Pick one of these that matches what you have installed:\" >&2\n echo \" export AGENTOPS_COMPILE_RUNTIME=claude-cli # uses local 'claude' binary, no API key needed\" >&2\n echo \" export AGENTOPS_COMPILE_RUNTIME=ollama # needs OLLAMA_HOST (default http://localhost:11434)\" >&2\n echo \" export AGENTOPS_COMPILE_RUNTIME=claude # needs ANTHROPIC_API_KEY\" >&2\n echo \" export AGENTOPS_COMPILE_RUNTIME=openai # needs OPENAI_API_KEY\" >&2\n echo \"\" >&2\n echo \"For interactive compilation, invoke /compile directly in a Claude Code session.\" >&2\n exit 1\n ;;\n esac\n}\n\n# --- Preflight: verify the selected runtime is usable ---\n\npreflight_runtime() {\n case \"$RUNTIME\" in\n claude-cli)\n if ! command -v claude &>/dev/null; then\n echo \"ERROR: runtime=claude-cli but 'claude' binary is not on PATH.\" >&2\n echo \"Install Claude Code or switch runtime: export AGENTOPS_COMPILE_RUNTIME=ollama\" >&2\n return 1\n fi\n ;;\n claude)\n if [[ -z \"${ANTHROPIC_API_KEY:-}\" ]]; then\n echo \"ERROR: runtime=claude but ANTHROPIC_API_KEY is not set.\" >&2\n echo \"Either export ANTHROPIC_API_KEY=... or switch: export AGENTOPS_COMPILE_RUNTIME=claude-cli\" >&2\n return 1\n fi\n ;;\n openai)\n if [[ -z \"${OPENAI_API_KEY:-}\" ]]; then\n echo \"ERROR: runtime=openai but OPENAI_API_KEY is not set.\" >&2\n return 1\n fi\n ;;\n ollama)\n if ! command -v curl &>/dev/null; then\n echo \"ERROR: runtime=ollama but curl is not on PATH.\" >&2\n return 1\n fi\n if ! curl -sf --max-time 2 \"$OLLAMA_API/api/tags\" >/dev/null 2>&1; then\n echo \"WARN: runtime=ollama but $OLLAMA_API did not respond to /api/tags (continuing anyway)\" >&2\n fi\n ;;\n \"\")\n echo \"ERROR: AGENTOPS_COMPILE_RUNTIME is not set. See 'ao compile --help' for options.\" >&2\n return 1\n ;;\n *)\n echo \"ERROR: unknown runtime '$RUNTIME'. Expected one of: ollama, claude, claude-cli, openai.\" >&2\n return 1\n ;;\n esac\n return 0\n}\n\n# --- Phase: Inventory ---\n\ninventory_sources() {\n local stored_hashes\n stored_hashes=$(load_hashes)\n local changed_files=()\n local unchanged_count=0\n\n local source_dirs=(\n \"$SOURCES_DIR/learnings\"\n \"$SOURCES_DIR/patterns\"\n \"$SOURCES_DIR/research\"\n \"$SOURCES_DIR/retros\"\n \"$SOURCES_DIR/forge\"\n \"$SOURCES_DIR/knowledge\"\n )\n\n for dir in \"${source_dirs[@]}\"; do\n [[ -d \"$dir\" ]] || continue\n while IFS= read -r -d '' file; do\n local current_hash\n current_hash=$(compute_hash \"$file\")\n local stored_hash\n stored_hash=$(get_stored_hash \"$file\" \"$stored_hashes\")\n\n if [[ \"$INCREMENTAL\" == \"true\" ]] && [[ \"$current_hash\" == \"$stored_hash\" ]]; then\n unchanged_count=$((unchanged_count + 1))\n else\n changed_files+=(\"$file\")\n fi\n done \u003c \u003c(find \"$dir\" -type f -name \"*.md\" -print0)\n done\n\n echo \"Changed: ${#changed_files[@]}, Unchanged: $unchanged_count\" >&2\n\n # Output changed files, one per line\n for f in \"${changed_files[@]}\"; do\n echo \"$f\"\n done\n}\n\n# --- Phase: Compile ---\n\ncompile_articles() {\n local changed_files=()\n while IFS= read -r line; do\n [[ -n \"$line\" ]] && changed_files+=(\"$line\")\n done\n\n if [[ ${#changed_files[@]} -eq 0 ]]; then\n echo \"No changed files to compile.\" >&2\n return 0\n fi\n\n # Explicit outer batching loop: chunk changed_files into slices of\n # $BATCH_SIZE and call compile_single_batch for each slice. Keeping the\n # loop explicit (no recursion, no prefix-env-assignment) makes the flow\n # testable and readable.\n local total=${#changed_files[@]}\n local bsize=${BATCH_SIZE:-25}\n if ! [[ \"$bsize\" =~ ^[0-9]+$ ]] || [[ \"$bsize\" -lt 1 ]]; then\n bsize=25\n fi\n if [[ \"$total\" -le \"$bsize\" ]]; then\n compile_single_batch \"${changed_files[@]}\"\n return $?\n fi\n\n echo \"Batching $total changed files into batches of $bsize...\" >&2\n local batch_index=0\n local i=0\n while [[ $i -lt $total ]]; do\n if [[ \"$MAX_BATCHES\" -gt 0 ]] && [[ $batch_index -ge \"$MAX_BATCHES\" ]]; then\n echo \"Reached --max-batches=$MAX_BATCHES; stopping after $batch_index batch(es). Remaining $((total - i)) files will be picked up on next run.\" >&2\n break\n fi\n local end=$((i + bsize))\n [[ $end -gt $total ]] && end=$total\n batch_index=$((batch_index + 1))\n echo \"Batch $batch_index: files $((i+1))..$end of $total\" >&2\n if ! compile_single_batch \"${changed_files[@]:i:bsize}\"; then\n echo \"Batch $batch_index failed; aborting.\" >&2\n return 1\n fi\n i=$end\n done\n echo \"Batched compile complete: $batch_index batch(es), $total file(s).\" >&2\n return 0\n}\n\n# compile_single_batch compiles one chunk of changed files in a single LLM\n# call. Callers (compile_articles) handle chunking; this function assumes\n# the argv list fits in one prompt.\ncompile_single_batch() {\n local changed_files=(\"$@\")\n if [[ ${#changed_files[@]} -eq 0 ]]; then\n return 0\n fi\n\n # Read all changed files into a single context\n local context=\"\"\n for f in \"${changed_files[@]}\"; do\n context+=\"\n--- FILE: $f ---\n$(cat \"$f\")\n\"\n done\n\n local system_prompt=\"You are a knowledge compiler. You read raw knowledge artifacts (learnings, research, patterns, retros) and compile them into encyclopedia-style wiki articles.\n\nRules:\n- Each article covers ONE topic/theme\n- Use [[wikilinks]] for cross-references between articles\n- Include a Sources section listing source files\n- Include a Related section with [[links]] to related topics\n- Write synthesis, not summaries — connect insights across sources\n- Use YAML frontmatter with title, compiled date, sources list, and tags\n- Article filenames should be kebab-case topic slugs (e.g., testing-strategy.md)\n\nIMPORTANT: Do NOT wrap your output in markdown code fences (\\`\\`\\`). Output raw article content directly after each === ARTICLE: marker.\"\n\n local user_prompt=\"Compile the following raw knowledge artifacts into wiki articles. Output each article separated by '=== ARTICLE: \u003cfilename> ===' markers.\n\n$context\n\nFor each article output:\n=== ARTICLE: \u003ctopic-slug>.md ===\n\u003cfull article content with frontmatter>\n\nAfter all articles, output:\n=== INDEX ===\n\u003cindex.md content cataloging all articles by category>\"\n\n local result\n result=$(llm_call \"$system_prompt\" \"$user_prompt\")\n\n # Parse result into individual files\n local current_file=\"\"\n local current_content=\"\"\n local written_count=0\n\n while IFS= read -r line; do\n if [[ \"$line\" =~ ^===\\ ARTICLE:\\ (.+)\\ ===$ ]]; then\n # Save previous article if exists\n if [[ -n \"$current_file\" ]] && [[ -n \"$current_content\" ]]; then\n echo \"$current_content\" > \"$OUTPUT_DIR/$current_file\"\n echo \"Compiled: $current_file\" >&2\n written_count=$((written_count + 1))\n fi\n current_file=$(basename \"${BASH_REMATCH[1]}\")\n current_content=\"\"\n elif [[ \"$line\" =~ ^===\\ INDEX\\ ===$ ]]; then\n # Save previous article\n if [[ -n \"$current_file\" ]] && [[ -n \"$current_content\" ]]; then\n echo \"$current_content\" > \"$OUTPUT_DIR/$current_file\"\n echo \"Compiled: $current_file\" >&2\n written_count=$((written_count + 1))\n fi\n current_file=\"index.md\"\n current_content=\"\"\n elif [[ \"$line\" =~ ^[[:space:]]*\\`\\`\\`(markdown)?[[:space:]]*$ ]]; then\n # Defense-in-depth: skip opening/closing markdown code fences that\n # some LLM runtimes (notably `claude -p`) wrap around the response.\n continue\n else\n current_content+=\"$line\n\"\n fi\n done \u003c\u003c\u003c \"$result\"\n\n # Save last article\n if [[ -n \"$current_file\" ]] && [[ -n \"$current_content\" ]]; then\n echo \"$current_content\" > \"$OUTPUT_DIR/$current_file\"\n echo \"Compiled: $current_file\" >&2\n written_count=$((written_count + 1))\n fi\n\n # Only persist hashes if this batch actually produced output. If the LLM\n # returned a malformed/empty response (or the batch was otherwise lost),\n # leave the input files' hashes alone so they get retried on the next run.\n # This is the Task A fix: files scheduled but not compiled must NOT have\n # their hashes saved, otherwise they are silently stranded forever.\n if [[ $written_count -gt 0 ]]; then\n save_hashes \"${changed_files[@]}\"\n else\n echo \"WARN: batch produced no articles; skipping hash persistence for ${#changed_files[@]} input file(s) so they retry next run.\" >&2\n fi\n\n # Append to log\n local article_count\n article_count=$(find \"$OUTPUT_DIR\" -name \"*.md\" ! -name \"index.md\" ! -name \"log.md\" ! -name \"lint-report.md\" | wc -l | tr -d ' ')\n local log_entry\n log_entry=\"## [$(date +%Y-%m-%d)] compile | $article_count articles from ${#changed_files[@]} sources\n- Compiled from: ${changed_files[*]}\n\"\n echo \"$log_entry\" >> \"$OUTPUT_DIR/log.md\"\n}\n\nsave_hashes() {\n local files=(\"$@\")\n local json=\"{\"\n local first=true\n\n for f in \"${files[@]}\"; do\n local h\n h=$(compute_hash \"$f\")\n if [[ \"$first\" == \"true\" ]]; then\n first=false\n else\n json+=\",\"\n fi\n json+=\"\\\"$f\\\":\\\"$h\\\"\"\n done\n\n json+=\"}\"\n\n # Merge with existing hashes\n if [[ -f \"$HASH_FILE\" ]]; then\n python3 -c \"\nimport json, sys\nhash_file = sys.argv[1]\nnew = json.loads(sys.argv[2])\nwith open(hash_file) as f:\n existing = json.load(f)\nexisting.update(new)\nwith open(hash_file, 'w') as f:\n json.dump(existing, f, indent=2)\n\" \"$HASH_FILE\" \"$json\"\n else\n echo \"$json\" | python3 -m json.tool > \"$HASH_FILE\"\n fi\n}\n\n# --- Phase: Lint ---\n\nlint_wiki() {\n local articles=()\n while IFS= read -r -d '' f; do\n articles+=(\"$f\")\n done \u003c \u003c(find \"$OUTPUT_DIR\" -name \"*.md\" ! -name \"index.md\" ! -name \"log.md\" ! -name \"lint-report.md\" ! -name \".hashes.json\" -print0)\n\n if [[ ${#articles[@]} -eq 0 ]]; then\n echo \"No articles to lint.\" >&2\n return 0\n fi\n\n local orphans=()\n local stale_claims=()\n\n for article in \"${articles[@]}\"; do\n local basename_article\n basename_article=$(basename \"$article\" .md)\n\n # Check for orphans: articles with no inbound [[wikilinks]]\n local inbound=0\n for other in \"${articles[@]}\"; do\n [[ \"$other\" == \"$article\" ]] && continue\n if grep -q \"\\[\\[$basename_article\\]\\]\" \"$other\" 2>/dev/null; then\n inbound=$((inbound + 1))\n break\n fi\n done\n if [[ $inbound -eq 0 ]]; then\n orphans+=(\"$basename_article\")\n fi\n\n # Check for stale code references\n while IFS= read -r ref; do\n if [[ -n \"$ref\" ]] && [[ ! -e \"$ref\" ]]; then\n stale_claims+=(\"$basename_article references $ref\")\n fi\n done \u003c \u003c(grep -oE '`[a-zA-Z0-9_./-]+\\.(go|py|sh|ts|js|yaml|json|md)`' \"$article\" 2>/dev/null | tr -d '`' || true)\n done\n\n # Write lint report\n cat > \"$OUTPUT_DIR/lint-report.md\" \u003c\u003c REPORT\n# Wiki Lint Report — $(date +%Y-%m-%d)\n\n## Orphan Pages: ${#orphans[@]}\n$(for o in \"${orphans[@]}\"; do echo \"- [[$o]]\"; done)\n\n## Stale Claims: ${#stale_claims[@]}\n$(for s in \"${stale_claims[@]}\"; do echo \"- $s\"; done)\n\n## Articles Scanned: ${#articles[@]}\nREPORT\n\n echo \"Lint complete: ${#orphans[@]} orphans, ${#stale_claims[@]} stale claims\" >&2\n}\n\n# --- Main ---\n\nmain() {\n echo \"=== Knowledge Compiler ===\" >&2\n echo \"Runtime: ${RUNTIME:-inline}\" >&2\n echo \"Sources: $SOURCES_DIR\" >&2\n echo \"Output: $OUTPUT_DIR\" >&2\n echo \"Incremental: $INCREMENTAL\" >&2\n echo \"Batch size: ${BATCH_SIZE}\" >&2\n\n if [[ \"$PREFLIGHT_ONLY\" == \"true\" ]]; then\n preflight_runtime\n return $?\n fi\n\n if [[ \"$LINT_ONLY\" == \"true\" ]]; then\n lint_wiki\n return 0\n fi\n\n # Verify runtime is configured before doing any work.\n preflight_runtime || return 1\n\n # Inventory → Compile → Lint\n local changed_files\n changed_files=$(inventory_sources)\n\n if [[ -n \"$changed_files\" ]]; then\n echo \"$changed_files\" | compile_articles\n else\n echo \"All source files unchanged — skipping compilation.\" >&2\n fi\n\n lint_wiki\n echo \"=== Compilation complete ===\" >&2\n}\n\nmain\n","content_type":"application/x-sh; charset=utf-8","language":"bash","size":16387,"content_sha256":"177a51e95a362eed738d1210fcc214ae590a5a454a71b32c1c325cff9545ae4f"},{"filename":"scripts/tests/test-fence-stripping.sh","content":"#!/usr/bin/env bash\n# test-fence-stripping.sh — empirically verify that the splitter in\n# compile.sh skips markdown code fences (```markdown / ```) emitted by\n# some LLM runtimes (notably `claude -p`).\n#\n# Standalone: does NOT source compile.sh (it tops-out in side-effect code);\n# instead it replicates the fence-skipping rule and asserts it matches\n# every fence variant we've seen in real smoke runs.\n\nset -euo pipefail\n\nSCRIPT_DIR=\"$(cd \"$(dirname \"${BASH_SOURCE[0]}\")\" && pwd)\"\nCOMPILE_SH=\"$SCRIPT_DIR/../compile.sh\"\n\n# 1. Static check: the splitter contains the fence-skipping clause.\nif ! grep -q 'markdown.*code fences' \"$COMPILE_SH\"; then\n echo \"FAIL: compile.sh splitter is missing fence-stripping clause\" >&2\n exit 1\nfi\n\n# 2. Static check: system prompt tells the LLM NOT to emit fences.\nif ! grep -q 'Do NOT wrap your output in markdown code fences' \"$COMPILE_SH\"; then\n echo \"FAIL: compile.sh system prompt is missing fence-suppression instruction\" >&2\n exit 1\nfi\n\n# 3. Behavioral check: the regex must match exactly the fence-lines we want\n# to strip and nothing else. Mirror the splitter's regex.\nfence_regex='^[[:space:]]*```(markdown)?[[:space:]]*

Important: agents should read /llm.txt, /llms.txt, or /.well-known/skills.json to discover the public Skillopedia API.

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Important: agents should read /llm.txt, /llms.txt, or /.well-known/skills.json to discover the public Skillopedia API.