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 pilotspace/pilot-space --skill ai-contextgit clone --depth 1 https://github.com/pilotspace/pilot-spaceWrote 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/pilotspace/pilot-space/ai-context)<a href="https://agentmods.dev/skills/pilotspace/pilot-space/ai-context"><img src="https://agentmods.dev/badge/skills/pilotspace/pilot-space/ai-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/pilotspace/pilot-space/ai-context"><img src="https://agentmods.dev/badge/skills/pilotspace/pilot-space/ai-context.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 | $0.00017 | $0.01998 |
| Opus 5.5 | $0.00007 | $0.00799 |
| Sonnet 5.5 | $0.00003 | $0.00400 |
| Haiku 4.5 | $0.00002 | $0.00200 |
Grade A, and why
ai-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 2mo 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 — 251 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI Context Skill
Generate comprehensive developer context for an issue: summary, complexity analysis, implementation tasks, related content, and a ready-to-use Claude Code prompt.
Quick Start
Use this skill when:
- Developer opens "AI Context" tab on an issue detail page
- User explicitly requests context generation (
/ai-context) - System needs structured implementation guidance for an issue
Example:
Issue: "PILOT-42: Implement real-time notifications"
AI generates:
- Summary: Architecture overview + scope analysis
- Complexity: high (cross-cutting: backend + frontend + infra)
- Tasks: 6 ordered subtasks with estimates and dependencies
- Claude Code Prompt: Ready-to-use implementation guide
Workflow
-
Analyze the Issue
- Read the issue title, description, and metadata
- Understand scope, complexity, and technical requirements
- Identify the technical layers involved (DB, API, Frontend, Tests)
-
Identify Related Content
- Use
search_issuesto find related or similar issues in the workspace - Use
search_notesto find relevant notes and documentation - Check for linked PRs, commits, and code references
- Use
-
Assess Complexity
- low: Single layer, straightforward implementation, 1-2 files
- medium: Multiple files, standard patterns, some cross-cutting
- high: Cross-layer changes, new architecture, significant testing
-
Generate Implementation Tasks
- Break down into ordered, actionable subtasks
- Identify dependencies between tasks (DAG structure)
- Estimate effort per task: S (~1h), M (~2-3h), L (~4-6h), XL (~8h+)
- Follow decomposition patterns:
- Backend: DB schema → Repository → Service → API → Tests
- Frontend: Component → State → Styling → Tests
- Full-stack: Backend → Frontend → Integration tests
-
Create Claude Code Prompt
- Summarize context for AI-assisted development
- List relevant code files and references
- Include implementation instructions and constraints
- Reference existing patterns and conventions
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.
- 2mo ago First seen · 251 lines · 17 tokens per session scan A 0c111983f783
ai-context is a skill published in the GitHub repository pilotspace/pilot-space (2 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 17 tokens to every session and 1,998 once invoked, about $0.0001 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 2026-08-31.
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