Expert
Consult GPT-5.6 Pro through the local `expert` CLI for second opinions on coding tasks. Use when the agent needs a high-quality external review, architecture/debugging help, test strategy feedback, implementation plan critique, or analysis of attached code/docs using explicit local files, directories, globs, or stdin. Especially useful for hard, ambiguous, high-risk, or long-running coding questions where a long blocking consult (up to 6 hours by default) is acceptable.From its SKILL.md
npx -y skills add bigblueboo/expert --skill expertAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
One thing to look at
- 0 stars0 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
SKILL.md
5.8 KB, ~1.3k tokens by cl100k_base, as published. Nobody here has run it
Expert
Use the expert CLI to ask GPT-5.6 Pro for a second opinion with explicit local context. The CLI uploads named files, starts a background Responses API job, polls until completion, and stores a resumable job record.
Quick Start
Prefer the installed binary when available:
expert ask "Review this implementation for correctness and missing tests." --file src/foo.ts --file test/foo.test.ts
If expert is not on PATH, run it via npx — no install required:
npx -y @bigblueboo/expert ask "Review this implementation for correctness and missing tests." --file src/foo.ts --file test/foo.test.ts
Consultation Workflow
-
Decide whether an external consult is appropriate.
- Use for hard debugging, architecture choices, security-sensitive code review, tricky API integration, migration plans, or test design.
- Do not use when the user forbids external API calls, when the task is trivial, or when sensitive secrets would need to be sent.
-
Gather focused context.
- Attach only files needed to answer the question.
- Prefer several exact files plus focused globs over one broad repository glob.
- Repeat
--filefor multiple files and globs; use directories when the relevant surface is broad. - Exclude generated output, vendored dependencies, large artifacts, and secrets.
-
Write a concrete prompt.
- Include the goal, constraints, known symptoms, what has already been tried, and the desired output shape.
- Ask for actionable findings, risks, and concrete next steps.
- For review requests, ask for prioritized bugs and missing tests before summary.
-
Run a dry run for broad context and check the token estimate.
expert ask "Check whether this refactor is safe." --file package.json --file "src/**/*.ts" --file "test/**/*.ts" --dry-run --format json
Check estimated_input_tokens in the output before sending. Trim the attachment list if it approaches the model's capacity (see Context Budget below).
- Run the consult and wait for the answer.
expert ask "Find correctness risks in this change. Return prioritized findings with file references." \
--file package.json \
--file "src/**/*.ts" \
--file "test/**/*.ts" \
--exclude "dist/**"
Command Patterns
Use stdin for long prompts or generated context:
git diff -- src test | expert ask "Review this diff for regressions and missing tests." --stdin --file package.json
Use JSON when another tool or script will consume the answer:
expert ask "Summarize API compatibility risks as JSON." --file src/api.ts --format json
Resume after interruption or timeout:
expert resume <job_id>
expert status <job_id>
expert cancel <job_id>
Tune blocking behavior only when needed (--timeout accepts s/m/h, default 360m):
expert ask "Deeply analyze this flaky test." --file test/flaky.test.ts --timeout 12h --poll-interval 5s
Context Budget
GPT-5.6 Pro has a 1,050,000-token context window shared by input, reasoning, and output (128,000 max output tokens). Do not exceed it:
- The CLI estimates input size (~4 characters per token) and refuses to send when the estimate exceeds 900,000 tokens. Prefer trimming the attachment list over raising
--max-context-tokens. - Requests whose input exceeds 272,000 tokens are billed by OpenAI at 2x input / 1.5x output for the entire request. Stay below that unless the extra context clearly earns its cost; the CLI warns when a consult crosses it.
- Byte-based estimates are unreliable for PDFs and other rich formats; leave extra headroom when attaching them.
- When context is too large, split the question into multiple focused consults instead of one oversized one, and summarize earlier answers in follow-up prompts.
Context Selection Guidance
- Include entrypoints, changed files, nearby tests, relevant configs, schemas, docs, and error logs.
- Include
package.json, lockfiles, or build configs when dependency or tooling behavior matters. - Include the failing command and concise output in the prompt or stdin.
- Avoid attaching
.env, credentials, private keys, customer data, build directories,node_modules, and unrelated repository snapshots. - For large repos, start with a dry run and narrow the attachment list before sending.
Interpreting Results
- Treat the consult as expert input, not automatic truth.
- Verify concrete claims against the local repo before editing.
- If the answer is incomplete or asks for more context, rerun
expert askwith the missing files and summarize the previous response in the new prompt. - If the terminal is interrupted, preserve the printed
expert resume <job_id>command. - If the consult exits with code 124, local polling timed out but the job is still running server-side; run the printed
expert resume <job_id>command (add--timeout 12hto wait longer). Under--format json, a timeout emits the envelope withtimed_out: true.
Defaults
The CLI defaults to gpt-5.6 with reasoning.effort: xhigh, background: true, store: true, a 360 minute (6 hour) timeout, a 5 second polling interval, and a 900,000-token estimated-input cap (--max-context-tokens). reasoning.mode defaults to pro for GPT-5.6 models (GPT-5.6 Pro) and standard for anything else. It requires OPENAI_API_KEY; job records are stored under ~/.expert/jobs unless EXPERT_HOME is set.
What ships with it: 1 file
249 B alongside SKILL.md
agents/
- openai.yaml249 B