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 agentmods add skills/mshadmanrahman/pm-pilot/deep-contextnpx skills add mshadmanrahman/pm-pilot --skill deep-contextgit clone --depth 1 https://github.com/mshadmanrahman/pm-pilotWrote 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/mshadmanrahman/pm-pilot/deep-context)<a href="https://agentmods.dev/skills/mshadmanrahman/pm-pilot/deep-context"><img src="https://agentmods.dev/badge/skills/mshadmanrahman/pm-pilot/deep-context.svg" alt="Measured on agentmods" 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 | $0.00058 | $0.01060 |
| Opus 5 | $0.00029 | $0.00530 |
| Sonnet 5 | $0.00012 | $0.00212 |
| Haiku 4.5 | $0.00006 | $0.00106 |
Grade A, and why
deep-context 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 5d 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.
How it starts
The opening of the file, as written. The whole thing — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deep Context
Comprehensive cross-channel research on any topic. Searches every connected tool in parallel, then synthesizes findings into a structured briefing. Use this when you need the full picture on a project, feature, incident, or initiative.
When to Activate
- User says "deep context on X", "tell me everything about X"
- User says "research X", "full context on X", "what do we know about X"
- User needs to get up to speed on an unfamiliar topic quickly
Input
Required:
- Topic: The subject to research (project name, feature, incident, concept, person)
Optional:
- Time range: How far back to search (default: 90 days)
- Depth: "quick" (summary only) or "deep" (full timeline + all sources, default)
Execution
Context Check
Before searching, read all four context files (context/company.md, context/product.md, context/competitors.md, context/personas.md) if they exist. Existing context informs search terms and avoids redundant research. After synthesis, offer to update context files with new knowledge discovered.
Step 1: Expand Search Terms
Before searching, generate 3-5 related search terms. Topics often have aliases, abbreviations, or related concepts.
Example: "authentication redesign" expands to: "auth redesign", "login", "SSO", "identity", "auth v2"
Step 2: Parallel Data Gathering (Fan-Out)
Search ALL connected MCP sources in parallel using each search term.
| Source | Method | What to Extract |
|---|---|---|
| Jira | JQL text search | Epics, stories, bugs, comments mentioning topic |
| Confluence | CQL text search | Specs, RFCs, design docs, meeting notes |
| Slack | Message search across channels | Discussions, decisions, announcements |
| GitHub | Code search, issue search, PR search | Implementation details, technical decisions |
| Gmail | Thread search | Stakeholder communications |
| Google Calendar | Event search | Meetings related to topic |
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.
- 5d ago First seen · 119 lines · 58 tokens per session scan A 8844c2e30811
deep-context is a skill published in the GitHub repository mshadmanrahman/pm-pilot (19 stars, last pushed 14d ago), licensed MIT. It adds 58 tokens to every session and 1,060 once invoked, about $0.0003 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.
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