pm-user-feedback

A workflow for collecting user feedback from tools such as Dovetail, Productboard, Notion, Linear, and GitHub, then grouping it into themes.

In plain words
What is it for?
Use it to create or refresh a Feedback page in a Nanopm wiki and compare feedback themes with the current roadmap.
Why use it?
It brings scattered feedback together and highlights the most important unresolved signals for product planning.

Skill for Claude CodeCodex

Part of the nanopm plugin — 26 skills, 1 hook shipped together

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 skills/nmrtn/nanopm/pm-user-feedback
Any agent
npx skills add nmrtn/nanopm --skill pm-user-feedback
Clone the repo
git clone --depth 1 https://github.com/nmrtn/nanopm

Made for: Claude Code, Codex.

Or install nanopm, the plugin that ships this one along with the rest of its 26 skills, 1 hook.

Per session 67 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,309 The whole file, excluding the scripts and references it only reads on demand.
Security scan C 2 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 $0.00067 $0.04309
Opus 5 $0.00034 $0.02155
Sonnet 5 $0.00013 $0.00862
Haiku 4.5 $0.00007 $0.00431

Measured 3d ago against content hash d19d7d34dbbd, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade C, and why

pm-user-feedback scanned grade C with 2 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 3d 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.

Downloads and executes remote codehighSupply chain

curl | sh runs whatever the server returns today, which is not necessarily what it returned when this was reviewed.

{ echo "ERROR: nanopm not installed. Run: curl -fsSL https://raw.githubusercontent.com/nmrtn/nanopm/main/setup | bash"; exit 1; }

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

{ echo "ERROR: nanopm not installed. Run: curl -fsSL https://raw.githubusercontent.com/nmrtn/nanopm/main/setup | bash"; exit 1; }
pm-user-feedback/SKILL.md · 384 lines

How it starts

The opening of the file, as written. The whole thing — 384 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Multi-host portability rules. When invoking AskUserQuestion:

  1. The header field MUST be a short noun phrase (≤ 12 characters). Mistral Vibe rejects longer headers with string_too_long. Pick from: Start, Target, Scope, Audience, Methodology, Feature, Question.
  2. The options list MUST have at least 2 items. Vibe rejects empty/single-option calls. For free-text input, always provide ≥ 2 framing options (e.g. Yes, here's the input / Skip) — never call ask_user_question with options: [].

Preamble (run first)

source ~/.nanopm/lib/nanopm.sh 2>/dev/null || \
  source .nanopm/lib/nanopm.sh 2>/dev/null || \
  { echo "ERROR: nanopm not installed. Run: curl -fsSL https://raw.githubusercontent.com/nmrtn/nanopm/main/setup | bash"; exit 1; }
nanopm_preamble

Phase 0: Prior context

source ~/.nanopm/lib/nanopm.sh 2>/dev/null || source .nanopm/lib/nanopm.sh 2>/dev/null || true
nanopm_context_read pm-user-feedback

If a prior entry exists: "Prior feedback snapshot from {ts}. Running a refresh — themes will be re-synthesized from current data."

Phase 1: Detect available sources

Check every potential feedback source:

source ~/.nanopm/lib/nanopm.sh 2>/dev/null || source .nanopm/lib/nanopm.sh 2>/dev/null || true
_TIER_DOVETAIL=$(nanopm_has_connector dovetail)
_TIER_NOTION=$(nanopm_has_connector notion)
_TIER_LINEAR=$(nanopm_has_connector linear)
_TIER_GITHUB=$(nanopm_has_connector github)

# Productboard: check MCP, API key, or browser
if grep -q "mcp__productboard__" CLAUDE.md 2>/dev/null; then
  _TIER_PRODUCTBOARD="1"
elif [ -n "${PRODUCTBOARD_TOKEN:-}" ]; then
  _TIER_PRODUCTBOARD="2"
elif [ -n "${B:-}" ]; then
  _TIER_PRODUCTBOARD=$(nanopm_config_get "productboard_url" | grep -q . && echo "3" || echo "3-discover")
else
  _TIER_PRODUCTBOARD="4"
fi

echo "DOVETAIL: $_TIER_DOVETAIL | PRODUCTBOARD: $_TIER_PRODUCTBOARD | NOTION: $_TIER_NOTION | LINEAR: $_TIER_LINEAR | GITHUB: $_TIER_GITHUB"

Read the full file on GitHub · 384 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. 3d ago First seen · 384 lines · 67 tokens per session scan C d19d7d34dbbd

Subscribe to this mod's changes

pm-user-feedback is a skill published in the GitHub repository nmrtn/nanopm (48 stars, last pushed 1mo ago), licensed MIT. It adds 67 tokens to every session and 4,309 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it C with 2 findings (downloads and executes remote code, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

brainstorming

You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.

obra/superpowers · 37 tokens

auto-perf-optimize

Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.

microsoft/vscode · 62 tokens

chat-perf

Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.

microsoft/vscode · 51 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens