team-attention/hoyeon/dev-scan

Dev Opinions Scan

Collect and synthesize diverse opinions on specific topics from multiple developer communities.

Purpose

Quickly understand diverse perspectives on technical topics:

• Distribution of pros/cons
• Practitioner experiences
• Hidden concerns or advantages
• Unique or notable perspectives

Runtime Surface

Claude Code

• Use the vendor scripts, WebSearch fallback, and hook-provided session ID as

described below.

• Claude Code may use multiple Bash calls, but shell-level parallelism must

happen inside one Bash invocation with & and wait.

Codex

• Use Bash-first vendor scripts. Do not add Hoyeon MCP for v1.
• If no hook-provided session ID exists, generate one with

date +%Y%m%d-%H%M%S and store run artifacts under $HOME/.hoyeon/codex-$RUN_ID/tmp/.

• Prefer node skills/dev-scan/vendor/chromux-search/web-search.mjs and the

bundled Python API scripts before using generic web search fallback.

• Treat ProductHunt as optional when PRODUCT_HUNT_TOKEN is missing.
• If dispatching internal research helpers, use Codex adapters when installed:

hoyeon-external-researcher, hoyeon-docs-researcher, or hoyeon-browser-explorer.

Data Sources

Execution

Step 0: Dependency Check

Run all checks in a single Bash call using shell backgrounding (& + wait). Claude Code executes Bash calls sequentially — multiple Bash tool calls do NOT run in parallel. The only way to parallelize is within one shell invocation.

mkdir -p /tmp/dev-scan-$$
 
# Kill existing chromux instance (may be non-headless) and relaunch in headless mode
chromux kill 2>/dev/null || true
chromux launch default --headless 2>/dev/null || true
 
node skills/dev-scan/vendor/chromux-search/web-search.mjs --check > /tmp/dev-scan-$$/web.txt 2>&1 &
python3 skills/dev-scan/vendor/hn-search/hn-search.py --check > /tmp/dev-scan-$$/hn.txt 2>&1 &
python3 skills/dev-scan/vendor/ph-search/ph-search.py --check > /tmp/dev-scan-$$/ph.txt 2>&1 &
wait
echo "=== Web (chromux) ===" && cat /tmp/dev-scan-$$/web.txt
echo "=== HN ===" && cat /tmp/dev-scan-$$/hn.txt
echo "=== ProductHunt ===" && cat /tmp/dev-scan-$$/ph.txt
rm -rf /tmp/dev-scan-$$

Report available sources before proceeding. Minimum 1 source required.

Step 1: Query Planning

Note: Step 0 (dependency check) and Step 1 (query planning) are independent — run Step 0 bash commands and perform Step 1 reasoning in the same message to save a round-trip.

1-1. Parse Request

Extract structured components from user request:

• topic: Main subject
• entities: Key product/technology names
• type: comparison | opinion | technology | event

Examples:

• "Developer reactions to React 19" → topic: React 19, entities: [React 19], type: opinion
• "Community opinions on Bun vs Deno" → topic: Bun vs Deno, entities: [Bun, Deno], type: comparison
• "What happened with Redis license" → topic: Redis license, entities: [Redis], type: event

1-2. Query Decomposition

User requests are often complex or conversational. Before generating platform-specific queries, decompose the request into atomic search concepts that search engines can match effectively.

Why this matters: Search engines match keywords, not intent. A verbose question like "Is React 19's use() hook a viable replacement for useEffect patterns in production apps?" will miss threads titled "use() vs useEffect" or "React 19 hooks review". Decomposition bridges this gap.

Process:

1. Extract core entities: Product/technology names exactly as communities write them
2. Generate query variants by search intent:

• core: The most concise keyword combination (2-4 words)
• versus: Direct comparison form if applicable ("A vs B")
• opinion: How people ask about it ("A worth it", "A review", "A experience")
• technical: Specific feature/aspect if the question targets one ("A feature X")

1. Select best variant per platform (see mapping below)

Example: "Can React 19's use() hook replace the existing useEffect pattern?"

Example: "Is Cursor worth paying for compared to GitHub Copilot?"

Example: "What happened with the Redis license change"

1-3. Source-Specific Query Mapping

Map the best variant from Step 1-2 to each platform's search behavior. Store all variants — the retry step (Step 2.5) needs alternate queries if the primary returns 0 results.

ProductHunt relevance check — PH is a product launch community. Only set Q_PH when the query involves specific products, tools, or SaaS (e.g. "Cursor", "Linear", "Supabase vs Firebase"). Skip PH when the topic is abstract/conceptual (e.g. "microservices best practices", "Rust async patterns", "tech layoffs").

Full example: user asks "claude code vs codex"

Decomposition: core=claude code codex, versus=claude code vs codex, opinion=claude code vs codex worth it

Step 1.5: Time Period

Extract time period from user request. Default: month.

Use TIME_PERIOD in all search commands below.

Step 2: Search (Two Bash Calls → File-Based)

Split into two phases: API sources in parallel (shell backgrounding), then all Google site: sources sequentially (chromux shares one Chrome instance — simultaneous use causes tab conflicts).

Results go to files, not stdout. Enriched JSON can exceed 50KB — piping to stdout hits Claude Code's output limit. Instead, save to files and use the Read tool to access them. This also serves as a log of the scan.

Both Bash calls must share the same temp directory. Generate a stable RUN_ID once and use it in both calls.

Bash call 1 — API sources (parallel):

SESSION_ID="[session ID from UserPromptSubmit hook]"
RUN_ID="dev-scan-$(date +%s)-$RANDOM"
D="$HOME/.hoyeon/$SESSION_ID/tmp/$RUN_ID"
mkdir -p "$D"
echo "$D" > /tmp/dev-scan-current-dir
 
python3 skills/dev-scan/vendor/hn-search/hn-search.py "{Q_HN}" --count 10 --comments 5 --time {TIME_PERIOD} --json > "$D/hn.json" 2>"$D/hn.err" &
python3 skills/dev-scan/vendor/ph-search/ph-search.py "{Q_PH}" --count 10 --comments 3 --time {TIME_PERIOD} --json > "$D/ph.json" 2>"$D/ph.err" &
wait
 
echo "RUN_DIR=$D"
for f in "$D"/*.json; do echo "$(basename $f): $(wc -c < $f) bytes, $(python3 -c "import json,sys; d=json.load(open('$f')); print(len(d) if isinstance(d,list) else 'obj')" 2>/dev/null || echo '?') items"; done

Bash call 2 — Google `site:` sources (sequential via chromux, same Bash call):

D="$(cat /tmp/dev-scan-current-dir)"
 
node skills/dev-scan/vendor/chromux-search/web-search.mjs "{Q_REDDIT}" --site reddit.com --time {TIME_SHORT} --count 5 --comments 5 --body 300 --json > "$D/reddit.json" 2>"$D/reddit.err"
node skills/dev-scan/vendor/chromux-search/web-search.mjs "{Q_TWITTER}" --site x.com --time {TIME_SHORT} --count 5 --comments 5 --json > "$D/x.json" 2>"$D/x.err"
node skills/dev-scan/vendor/chromux-search/web-search.mjs "{Q_DEVTO}" --site dev.to --time {TIME_SHORT} --count 5 --comments 5 --body 300 --json > "$D/devto.json" 2>"$D/devto.err"
node skills/dev-scan/vendor/chromux-search/web-search.mjs "{Q_LOBSTERS}" --site lobste.rs --time {TIME_SHORT} --count 5 --comments 5 --json > "$D/lobsters.json" 2>"$D/lobsters.err"
node skills/dev-scan/vendor/chromux-search/web-search.mjs "{Q_THREADS}" --site threads.net --time {TIME_SHORT} --count 5 --comments 5 --body 300 --json > "$D/threads.json" 2>"$D/threads.err"
 
for f in "$D"/*.json; do echo "$(basename $f): $(wc -c < $f) bytes, $(python3 -c "import json,sys; d=json.load(open('$f')); print(len(d) if isinstance(d,list) else 'obj')" 2>/dev/null || echo '?') items"; done

Reading results: Use the Read tool on each $D/{source}.json file. Read the files with the most items first (Reddit, Dev.to tend to be richest). Skip files with 0 items.

`TIME_SHORT` mapping: month→m, week→w, year→y, all→a (web-search.mjs uses single-letter time codes).