send-feedback

A guided command for reporting a bug, feature request, or question about the rn-dev-agent plugin. It gathers sanitized environment details and creates a GitHub issue.

In plain words
What is it for?
Use it to submit plugin feedback, describe reproduction steps and workarounds, link related issues, or request a new capability.
Why use it?
It reduces the effort of preparing a useful report while keeping home paths, secrets, personal information, and IP addresses out of the submitted data.

Command

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add commands/lykhoyda/rn-dev-agent/send-feedback
Clone the repo
git clone --depth 1 https://github.com/Lykhoyda/rn-dev-agent
Per session 39 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,575 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00039 $0.02575
Opus 5 $0.00019 $0.01288
Sonnet 5 $0.00008 $0.00515
Haiku 4.5 $0.00004 $0.00258

Measured 2d ago against content hash c25bcc5bfe4f, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

send-feedback scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

packages/claude-plugin/commands/send-feedback.md · 258 lines

How it starts

The opening of the file, as written. The whole thing — 258 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Send Feedback — Sanitized Bug Report / Feature Request

Guide the user through submitting feedback for the rn-dev-agent plugin. All data is sanitized before submission — no home paths, secrets, PII, or IP addresses leave the local machine.

Step 0: Check for pre-written context

If $ARGUMENTS is provided, use it as the starting description. Scan the argument text for clues about type (bug/feature/question), steps to reproduce, workarounds, related issues, and suggested fixes. Pre-fill as much as possible so the user only confirms rather than re-typing.

Step 1: Gather feedback details

Ask: "What would you like to report?"

  • Bug report — something broken or unexpected
  • Feature request — something missing or could be improved
  • Question — need help understanding something

Then collect the following (skip what was already provided via $ARGUMENTS):

  1. Description (1-3 sentences) — what happened or what's needed
  2. Steps to reproduce (for bugs) — numbered list of steps. Ask: "How can I reproduce this?"
  3. Known workaround (optional) — "Did you find a workaround or fix?"
  4. Related issues (optional) — "Any related GitHub issues? (e.g., #22, #23)"
  5. Suggested fix (optional, for bugs) — "Do you know what should change?"

Step 2: Collect environment context (automated)

Call rn_session with action: "status" first. Its public authority projection returns the exact session's opaque sessionId; retain it locally and pass it only to the collector process as RN_DEV_AGENT_SESSION_ID; do not include the ID in the preview or submission. This keeps feedback authority aligned after a handoff, when multiple released sessions can share one worktree.

Run the collection script from the project root to gather sanitized environment data:

PLUGIN_ROOT="${RN_DEV_AGENT_CODEX_PLUGIN_ROOT:-${CODEX_PLUGIN_ROOT:-${CLAUDE_PLUGIN_ROOT:-}}}"
PROJECT_ROOT="${RN_PROJECT_ROOT:-${CLAUDE_USER_CWD:-$PWD}}"
if [ -z "$PLUGIN_ROOT" ] && [ -f "packages/codex-plugin/.codex-plugin/plugin.json" ]; then
  PLUGIN_ROOT="packages/codex-plugin"
fi
if [ -z "$PLUGIN_ROOT" ]; then
  PLUGIN_MANIFEST="$(find "${CODEX_HOME:-$HOME/.codex}/plugins/cache" -path "*/rn-dev-agent/*/.codex-plugin/plugin.json" 2>/dev/null | sort -V | tail -n 1)"
  [ -n "$PLUGIN_MANIFEST" ] && PLUGIN_ROOT="$(dirname "$(dirname "$PLUGIN_MANIFEST")")"
fi
if [ -n "$PLUGIN_ROOT" ] && [ -x "$PLUGIN_ROOT/scripts/collect-feedback.sh" ]; then
  (cd "$PROJECT_ROOT" && RN_DEV_AGENT_SESSION_ID="<exact rn_session sessionId>" \
    "$PLUGIN_ROOT/scripts/collect-feedback.sh")
elif command -v rn-collect-feedback >/dev/null 2>&1; then
  (cd "$PROJECT_ROOT" && RN_DEV_AGENT_SESSION_ID="<exact rn_session sessionId>" \
    rn-collect-feedback)
else
  echo "rn-dev-agent feedback collector is missing; reinstall or update the plugin" >&2
  exit 1
fi

Read the full file on GitHub · 258 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 258 lines · 39 tokens per session scan A c25bcc5bfe4f

Subscribe to this mod's changes

send-feedback is a command published in the GitHub repository Lykhoyda/rn-dev-agent (11 stars, last pushed 2d ago), licensed MIT. It adds 39 tokens to every session and 2,575 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.