Borrowing it
Nothing to install: this file belongs to Alexander-M-Dickerson/ai-asset-pricing. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Alexander-M-Dickerson/ai-asset-pricing/main/.claude/skills/sync-context/SKILL.mdgit clone --depth 1 https://github.com/Alexander-M-Dickerson/ai-asset-pricingWrote 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/alexander-m-dickerson/ai-asset-pricing/sync-context)<a href="https://agentmods.dev/skills/alexander-m-dickerson/ai-asset-pricing/sync-context"><img src="https://agentmods.dev/badge/skills/alexander-m-dickerson/ai-asset-pricing/sync-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/alexander-m-dickerson/ai-asset-pricing/sync-context"><img src="https://agentmods.dev/badge/skills/alexander-m-dickerson/ai-asset-pricing/sync-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 | $0.00045 | $0.00601 |
| Opus 5 | $0.00023 | $0.00300 |
| Sonnet 5 | $0.00009 | $0.00120 |
| Haiku 4.5 | $0.00005 | $0.00060 |
Grade A, and why
sync-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 13d 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 — 78 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Context Sync
Detect and fix documentation drift across the repo's AI context layer.
Examples
/sync-context— scan all mappings and propose updates/sync-context pybondlab— scan only PyBondLab-related mappings
Hard Rules
- NEVER auto-commit doc updates. Always show the proposed edit and wait for approval.
- NEVER rewrite entire documents. Propose targeted, minimal edits only.
- Preserve the voice and judgment in existing docs — update facts, not opinions.
- If a doc references a file that no longer exists, flag it but do not remove without asking.
- Do not add new sections or restructure documents unless the drift requires it.
Workflow
1. Run Drift Detection
"<PYTHON>" tools/context_drift.py --json
Parse the JSON output. Each entry has: source (glob), doc (file path), days_stale (float).
If $ARGUMENTS contains a keyword (e.g., pybondlab), filter to entries where
either source or doc contains that keyword. Otherwise process all entries.
2. For Each Stale Mapping
For each drift warning, in order:
-
Read the current doc using the Read tool.
-
Identify what changed in the source since the doc was last updated:
git log --oneline --since="<days_stale> days ago" -- <source_files>Then read the relevant source files to understand the current state.
-
Compare what the doc says against the current source state. Identify specific lines in the doc that are now inaccurate, incomplete, or misleading.
-
Propose a targeted edit — show the old text and the proposed replacement. Use the Edit tool format (old_string → new_string). Explain the reason for each change in one sentence.
-
Wait for user approval before applying each edit.
3. Summary
After processing all mappings, print a summary table:
| Doc | Status | Action |
|------------------------|----------|-------------------------------------------|
| docs/ai/onboarding.md | Updated | bootstrap.py uv changes reflected |
| docs/ai/pybondlab.md | Current | no drift detected |
| AGENTS.md | Skipped | user declined update |
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.
- 13d ago First seen · 78 lines · 45 tokens per session scan A 18bdd98979b9
sync-context is a skill published in the GitHub repository Alexander-M-Dickerson/ai-asset-pricing (59 stars, last pushed 4mo ago), licensed MIT. It adds 45 tokens to every session and 601 once invoked, about $0.0002 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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