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 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/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/mshadmanrahman/pm-pilot/deep-context"><img src="https://agentmods.dev/badge/skills/mshadmanrahman/pm-pilot/deep-context.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00058 | $0.01060 |
| Opus 5.5 | $0.00023 | $0.00424 |
| Sonnet 5.5 | $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 1mo 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.
- 1mo 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 (22 stars, last pushed 23d ago), licensed MIT. It adds 58 tokens to every session and 1,060 once invoked, about $0.0002 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 2026-08-30.
Other skills, from other repositories
plan-growth-loop
Generate prioritized growth loops with implementation roadmaps based on codebase analysis. Use when the user says "plan", "growth loops", "prioritize", "what should I build", or "roadmap".
validate-loop
Check if growth loop requirements are actually implemented in the codebase. Use when the user says "validate", "check status", "skene status", "is it done", or "verify implementation".
ops-opnsense
OPNsense configuration via Terraform. Trigger for interfaces, firewall, NAT, DHCP/DNS, aliases.
agent-teams
Multi-agent team orchestration with native Agent Teams. Trigger when the user wants to launch a team of agents, coordinate parallel work with inter-agent communication, or use swarm mode.
dev-auth
Modern web auth implementation (better-auth, NextAuth/Auth.js, Clerk, Supabase Auth; migrating off the deprecated Lucia). Trigger when the user wants to add login, signup, sessions, OAuth, magic links, 2FA, or when existing auth code is detected to audit or migrate.
dev-debug
Systematic debugging - reproduce, isolate the root cause, fix, pin it with a regression test. Use it first whenever the user reports a bug, a crash, an error message, a wrong result or a failing test (a failing CI pipeline is ops-ci-fix), before reading code to guess at the cause.