PM Skills is a collection of plain-Markdown instructions that teach AI assistants structured methods for handling professional, personal, and life-admin tasks. People use it with Claude, ChatGPT, Gemini, Cursor, Codex, and other supported agents for work such as writing product requirements, reviewing documents, or planning difficult situations.
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.
npx skills add mohitagw15856/pm-claude-skills --skill multi-source-signal-synthesisergit clone --depth 1 https://github.com/mohitagw15856/pm-claude-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/mohitagw15856/pm-claude-skills/multi-source-signal-synthesiser)<a href="https://agentmods.dev/skills/mohitagw15856/pm-claude-skills/multi-source-signal-synthesiser"><img src="https://agentmods.dev/badge/skills/mohitagw15856/pm-claude-skills/multi-source-signal-synthesiser/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/mohitagw15856/pm-claude-skills/multi-source-signal-synthesiser"><img src="https://agentmods.dev/badge/skills/mohitagw15856/pm-claude-skills/multi-source-signal-synthesiser.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00098 | $0.00970 |
| Opus 5.5 | $0.00039 | $0.00388 |
| Sonnet 5.5 | $0.00020 | $0.00194 |
| Haiku 4.5 | $0.00010 | $0.00097 |
Grade A, and why
multi-source-signal-synthesiser 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- multi-source-signal-synthesiser — 86% identical, 9 lines differ
How it starts
The opening of the file, as written. The whole thing — 78 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Multi-Source Signal Synthesiser Skill
Reconcile user signals from multiple sources — interviews, support tickets, NPS, app reviews, sales calls — into a unified, weighted insight brief that surfaces the underlying need rather than the surface-level request.
Required Inputs
Work from what is given. If any of these is missing, still produce the complete output: fill each gap with a reasonable assumption marked (assumed, confirm) and list those assumptions at the end. Ask a question first only when the core subject itself is missing (there is nothing to write about).
- Signal sources (interviews, support tickets, NPS verbatims, app reviews, sales calls, analytics — any combination)
- Time period covered by the data
- Product area or feature the signals relate to (if scoped)
Source Weighting (default — adapt to context)
| Source | Weight | Rationale |
|---|---|---|
| Direct research (interviews, usability tests) | 5 | Highest-fidelity, structured |
| Support tickets (unprompted pain signals) | 4 | Real pain, unfiltered |
| NPS verbatims | 3 | Broad but shallow |
| App store reviews | 2 | Public, self-selected |
| Sales call summaries | 2 | Filtered through sales lens |
| Anecdote or single report | 1 | Low confidence alone |
Process
- Tag each signal by source and apply weight
- Look for convergence: same underlying need appearing across 3+ sources
- Look for divergence: contradictory signals suggesting user segmentation
- Distinguish surface request from underlying need (e.g. "faster export" may mean "I don't trust the data will be there when I need it")
- Produce ranked insights by weighted frequency
- Validate — Confirm each insight has evidence from at least 2 source types. Flag any insight resting on a single source as low-confidence.
Output Structure
User Signal Synthesis — [Date / Period]
Sources included: [list with count per source] Total signals processed: [n]
Insight 1: [Underlying need, not feature request]
- Confidence: High / Medium / Low (based on source diversity and weight)
- Evidence: [Signals from each source supporting this]
- Conflicting signals: [Any contradicting evidence and how to interpret it]
- Product implication: [Specific next step, not generic]
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.
- 2d ago First seen · 78 lines · 98 tokens per session scan A 3c0582f068d7
multi-source-signal-synthesiser is a skill published in the GitHub repository mohitagw15856/pm-claude-skills (1,449 stars, last pushed yesterday), licensed MIT. It adds 98 tokens to every session and 970 once invoked, about $0.0004 per session on Opus 5.5. 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 2026-10-12.
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