Borrowing it
Nothing to install: this file belongs to pskoett/measuring-ai-proficiency. 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/pskoett/measuring-ai-proficiency/main/.claude/skills/context-surfing/SKILL.mdgit clone --depth 1 https://github.com/pskoett/measuring-ai-proficiencyWrote 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/pskoett/measuring-ai-proficiency/context-surfing)<a href="https://agentmods.dev/skills/pskoett/measuring-ai-proficiency/context-surfing"><img src="https://agentmods.dev/badge/skills/pskoett/measuring-ai-proficiency/context-surfing/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/pskoett/measuring-ai-proficiency/context-surfing"><img src="https://agentmods.dev/badge/skills/pskoett/measuring-ai-proficiency/context-surfing.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 | $0.00144 | $0.04295 |
| Opus 5 | $0.00072 | $0.02148 |
| Sonnet 5 | $0.00029 | $0.00859 |
| Haiku 4.5 | $0.00014 | $0.00430 |
Grade A, and why
context-surfing 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 10d 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 — 376 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Context Surfing
Install
npx skills add pskoett/pskoett-ai-skills/skills/context-surfing
The agent rides the wave of peak context. When the wave crests, it commits. When it detects drift, it pulls out cleanly — saving state, handing off, and letting the next session catch the next wave.
No wipeouts. No zombie sessions. Only intentional, high-fidelity execution.
Mental Model
Think of context like an ocean wave:
- Paddling in = loading the intent frame, plan, and initial context. Energy is building.
- The peak = full context coherence. The agent knows exactly what it's doing and why. This is when to execute.
- The shoulder = context starting to flatten. Still rideable, but output density is dropping.
- The close-out = drift. Contradiction, hedging, second-guessing, or hallucinated details. Wipe-out territory.
The skill's job: ride as long as the wave is good, exit before it closes out.
Lifecycle Position
[plan-interview] → [intent-framed-agent] → [context-surfing ACTIVE] → [simplify-and-harden] → [self-improvement]
Context Surfing is the execution layer. It wraps all work between intent capture and post-completion review. Simplify-and-harden and self-improvement are the next steps in the pipeline — they run after context-surfing completes, not as conditions that end it.
Relationship with intent-framed-agent
Both skills are live during execution. They monitor different failure modes:
- intent-framed-agent monitors scope drift — am I doing the right thing? It fires structured Intent Checks when work moves outside the stated outcome.
- context-surfing monitors context quality drift — am I still capable of doing it well? It fires when the agent's own coherence degrades (hallucination, contradiction, hedging).
They are complementary, not redundant. An agent can be perfectly on-scope while its context quality degrades (e.g., it's doing the right thing but starting to hallucinate details). Conversely, scope drift can happen with perfect context quality (the agent deliberately chases a tangent). Intent-framed-agent's Intent Checks continue firing alongside context-surfing's wave monitoring.
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.
- 10d ago First seen · 376 lines · 144 tokens per session scan A a985c4afdcce
context-surfing is a skill published in the GitHub repository pskoett/measuring-ai-proficiency (11 stars, last pushed 1mo ago), licensed MIT. It adds 144 tokens to every session and 4,295 once invoked, about $0.0007 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 2026-08-31.
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