Anthropic cut 80% of Claude Code's system prompt: how to audit your own skills and CLAUDE.md with /doctor

What Anthropic reportedly changed

He cites an Anthropic engineer's post on context engineering for Claude 5 generation models: the Claude Code team cut over 80% of the system prompt for Opus 5 and Fable 5 and 5.1 with no measurable loss on its own evals. We could not reach Anthropic's original post to check the wording, but aiweekly and other write-ups report the same figure, so read the original before relying on it. His summary of the idea:

• Rules written for weaker models become restrictive. His example: a hard limit on code comments was replaced by an instruction to follow the style of the surrounding code.
• Use the smallest context that gets the result you want. "Minimal" doesn't mean short: if the model needs a detail, keep it.
• Define what done looks like: the outcome, why you want it, and the constraints it must respect, then leave room for the work.
• Load on demand. He cites Anthropic's finding that loading MCP tool definitions only when needed cut token use by 85% in their example and raised MCP evaluation scores (49% to 74% on Opus 4, 79.5% to 88.1% on Opus 4.5). Those are Anthropic's reported numbers for those older models. He also cites a 2025 paper where accuracy fell as input grew, but says that is no prediction for trimming your own CLAUDE.md.

What to keep and what to cut in your own setup

• Keep what the model can't infer: your voice, goals, audience, how the business works, and the why behind a task ("a student resource guide" changes the analogies and examples it picks).
• Cut rules added after one old mistake that now sit in CLAUDE.md, a skill and a third copy somewhere else, and anything Claude can look up itself, such as a long folder listing.
• Keep CLAUDE.md as a starting point: what the project is for, the gotchas and landmines, and pointers to deeper instructions. Move detailed procedures, such as a whole video-editing process, so they load only when you are doing that job.
• His experiment: he ran the same job (turn an interview into a student resource guide) with his full setup and with a fresh one. The full setup made the prettier, branded document; the fresh one produced the better structure, with ideas organised and timestamps added. His fix is a skill that fixes the branding (header, font, footer, logos) and states the intent, but leaves the content structure to the model.
• He also repeats a remark attributed to Boris Cherny, creator of Claude Code, that you should delete your skills every six months. We haven't checked that against a primary source.

Let /doctor do the audit

/doctor
/doctor prompt-audit [path]

He runs /doctor in a new session. Claude Code's command reference describes it as a setup checkup that diagnoses installation, settings, extension and CLAUDE.md problems and proposes fixes Claude applies after you confirm; /checkup is an alias. The same page lists a prompt-audit subcommand that audits your instructions, requiring Claude Code v2.1.283 or later. He doesn't use it in the video, so test it yourself. What his run reported:

• Skills table: each skill with where it is installed, how many recorded uses since installation, and an estimate of the tokens its listing costs (the front matter used to find the skill, not the full body that loads when it runs). Example sizes: 111 and 103 tokens, both with zero uses. It flagged 18 older skills with no recorded use and spared ones created days earlier. He still reviews the list before disabling anything, especially skills he uses through another tool. It drew on 50 recent sessions plus lifetime counters.
• Duplication: a project map repeating a routing map, plus repeated template, reference and archiving sections: about 2,250 characters of cuts, or roughly 563 tokens.
• Where memory comes from: project CLAUDE.md, user-wide instructions, the auto-memory index and the local CLAUDE.md. It also found a CLAUDE.md from a separate video project folder that was loading into his sessions, around 2,000 tokens he didn't know he was paying for.
• Broken skills: two with problems Claude couldn't see past: a wrong file name, and a formatting error in the front matter so the description never loaded.
• It also checked installation, automatic updates, auto mode, permissions and hooks, and offered to fix everything at the end.

The audit prompt, and the cadence

After the checkup he asked Claude Code to audit one workflow, read-only:

Audit this repo and show me the smallest change that would make the path
from a raw YouTube idea to a filming-ready script faster. Use the systems
already here. Cite the exact files you would reuse and do not edit anything yet.

It mapped the steps from idea to research, outline, script and teleprompter file, and found a handoff gap: the outline skill could gather facts but didn't require saving evidence in a file the script skill checked, while the script skill had a hard rule to re-verify facts. Of 25 video folders with a script, only three had a sources.md. It proposed three edits across two skills, and he approved them. His cadence: monthly if you add skills often, quarterly otherwise, and every time you switch to a new model. Once you trust it, run the checkup as a local scheduled task in the Claude desktop app and approve or reject the recommendations when you wake up.

Gotchas & Caveats

• Do not delete a skill just because it shows zero recorded uses; usage counted only covers what Claude Code recorded, not other tools.
• The 80% figure is Anthropic's report about its own product's prompt for specific models. It does not say your CLAUDE.md is too long; he tested only one workflow.
• The video includes a sponsor segment and a community pitch, which are not part of the method.
• Review any fix /doctor proposes before accepting it; fixes are applied after you confirm.

Key Takeaways

• After a model upgrade, re-test your skills and CLAUDE.md against a fresh setup and delete the rules the new model no longer needs.
• Keep context only you can supply, plus the reason behind the task; load procedures only for the job that needs them.
• Run /doctor to find unused skills, duplicated instructions, stray CLAUDE.md files and broken front matter.
• Make handoffs between skills explicit: write evidence to a file the next step reads.