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 glebis/claude-skills --skill context-buildergit clone --depth 1 https://github.com/glebis/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/glebis/claude-skills/context-builder)<a href="https://agentmods.dev/skills/glebis/claude-skills/context-builder"><img src="https://agentmods.dev/badge/skills/glebis/claude-skills/context-builder.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 163 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.01425 |
| Opus 5 | $0.00029 | $0.00713 |
| Sonnet 5 | $0.00012 | $0.00285 |
| Haiku 4.5 | $0.00006 | $0.00143 |
Grade A, and why
context-builder 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 8d 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 — 174 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Context Builder
Generate interactive context-building prompts for consulting clients. These prompts are designed to be run in Claude Code -- they guide a team through structured questions using AskUserQuestion, generate output files per section, and compile everything into a reusable CLAUDE.md.
Workflow
Phase 1: Intake (AskUserQuestion)
Ask all intake questions using AskUserQuestion with closed-list options. Gather:
Question 1: Company identifier
- Options: "I have a website URL", "I have a company name", "I have both"
- Follow up to get the actual URL/name
Question 2: Who will use this prompt?
- Options: "Specific person (name + role)", "A team (no specific person)", "Unknown / TBD"
- If specific person: follow up for name and role
Question 3: Primary consulting focus (multiSelect)
- "AI automation of current operations"
- "Existential strategy (what survives AI)"
- "New business models / pivots"
- "Product development with AI"
Question 4: Industry
- "Marketing / Advertising"
- "Manufacturing / Construction"
- "SaaS / Software"
- "Professional Services / Consulting"
- (Other)
Question 5: Existing context in vault?
- "Yes, there's a call transcript"
- "Yes, there are notes/files"
- "No existing context"
- If yes: ask for filename or search term to locate it
Question 6: Session language
- "Russian (questions in Russian, output in English)"
- "English throughout"
- "Other"
Phase 2: Research (automated)
Run these research steps in parallel where possible:
-
Web research: Use WebSearch and WebFetch (via Task agent) to gather:
- What the company does, products/services
- Target market, company size, geography
- Tech stack, partnerships
- Recent news, funding, team info
- Competitive landscape
-
Vault search: Search the Obsidian vault for:
- Transcripts mentioning the company name (Grep in vault root and Daily/)
- People files for contacts at the company (People/ folder)
- Any existing notes or research
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 8d ago First seen · 174 lines · 58 tokens per session scan A b6dbcef48adf
context-builder is a skill published in the GitHub repository glebis/claude-skills (374 stars, last pushed 6d ago), licensed MIT. It adds 58 tokens to every session and 1,425 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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