challenge

name	challenge
description	Generate idiom drills grounded in specific lines of a source file. Seeded patterns first, model eyeball fallback on no match. Grades user attempts /10 and writes outcomes to ~/.chiron/profile.json.

$challenge — hero feature: drills from your own code

Step 0 — Load project context

Check if .chiron-context.md exists in the project root.

If it exists: Read it. This file is your complete project reference. DO NOT scan the codebase, list directories, or re-read config files. The only additional file you read is the target source file from Step 1. Proceed to Step 1.

If it does NOT exist: Tell the user: "No project context found. Run $teach-chiron first." Then stop.

┌──────────────────────────────────────────────┐
│  $challenge                                  │
├──────────────────────────────────────────────┤
│  REQUIRES .chiron-context.md                 │
│  Run $teach-chiron once to generate it       │
├──────────────────────────────────────────────┤
│  CORE (always active)                        │
│  ✓ Language pack seeded pattern matching     │
│  ✓ Eyeball fallback for unmatched files      │
│  ✓ /10 grading + profile logging             │
├──────────────────────────────────────────────┤
│  ENHANCED (with rich project context)        │
│  + Project-aware drill targeting             │
│  + Concept pack auto-detection from imports  │
│  + Convention-aligned grading feedback        │
└──────────────────────────────────────────────┘

$challenge reads a source file, finds 1–3 concrete practice targets grounded in specific lines, and presents them as short drills you can complete in 5–15 minutes. Each drill is tied to an idiom from the language pack. Your attempts get graded /10 with honest, specific feedback.

Usage

• $challenge — drill on the current file in focus
• $challenge path/to/file.go — drill on a specific file
• $challenge functionName — locate the named function in the current file and drill on it

The arguments

$ARGUMENTS

---

CRITICAL — user instructions always win

Before anything else, check AGENTS.md. If user instructions conflict with this command's behavior — e.g., "just fix my code directly, don't drill me" — follow the user. Switch to a direct fix-and-explain mode, skip drill generation, and don't write to the profile file.

---

Current level

Apply the voice level from .chiron-context.md (the "Chiron config" section). The level affects voice tone of drill presentation and grading, how quickly you show the full solution, and how you respond to "just show me" requests. If missing or unrecognized, use default.

---

Step 0.5 — Load learning profile (best-effort)

Read ~/.chiron/profile.json if it exists. This is a best-effort read — the skill must work normally even if the profile is missing, corrupt, or empty. Parse the JSON and extract entries relevant to this session:

1. Filter by language/domain: Only entries whose tag matches the current file's language (e.g., go:* for Go files) or a loaded concept pack's domain (e.g., db:*, api:*).
2. Filter by recency: Entries from the last 30 days count at full weight. Older entries count at half weight. Do not discard old entries — the Ebbinghaus forgetting curve says old mistakes still matter, just less.
3. Build a weakness map: For each tag, count weighted drill_attempted + drill_gaveup as failures, weighted drill_solved as successes. A tag is a recurring weakness if: failures ≥ 2 AND failures/total > 0.5.
4. Build a mastery set: Tags with 2+ recent drill_solved and zero recent failures are "mastered — avoid re-drilling."

Error handling (silent fallback — never crash):

• File does not exist → empty weakness map, empty mastery set, proceed normally to Step 1
• File is not valid JSON → empty maps, proceed
• File has unexpected schema (missing entries, wrong types) → empty maps, proceed
• File is very large (>500 entries) → read last 200 entries only for relevance calculation
• Any other error → empty maps, proceed

The weakness map and mastery set are optional inputs to Steps 4–6. Missing profile just means no bias — /challenge behaves exactly as it did before the read-loop was added. Never block drill generation waiting for profile data.

Read-only: /challenge still writes to profile.json in Step 8, but that is the only writer. Step 0.5 never modifies the file.

---

Step 1 — Target resolution

From $ARGUMENTS, determine the target file:

• Empty arguments → use the file currently in focus in the conversation. If there's no file in focus, respond: "No file in focus. Run $challenge path/to/file.ext with a file path." and stop.
• Arguments look like a path (contain / or \ or a file extension) → treat as a file path and read it.
• Arguments look like a function name (identifier only, no slashes, no extension) → locate the function in the current file and drill on just that function.

If the target file cannot be read, respond with a clear error message (include the path you tried) and stop. Do not generate drills speculatively.

Step 2 — Language detection

Detect the language from the file extension:

• .go → Go

• .rs → Rust

• .py → Python

• .js, .mjs, .cjs → JavaScript

• .ts, .tsx → TypeScript (TypeScript pack + JavaScript pack both apply)

• .java → Java

• .cs → C#

• .kt, .kts → Kotlin

• .swift → Swift

• Any other extension → respond:

  chiron ships with language packs for Go, Rust, Python, JavaScript, TypeScript, Java, C#, Kotlin, and Swift. Community contributions for other languages are welcomed — see docs/CONTRIBUTING-LANGUAGE-PACKS.md.

  Then stop.

Step 3 — Load the language pack

Use the Read tool to load the language pack file for the detected language:

.codex/skills/challenge/packs/<language>.md

Where <language> is the lowercase name from Step 2: go, rust, python, javascript, typescript, java, csharp, kotlin, or swift.

For TypeScript/TSX files: read BOTH .codex/skills/challenge/packs/typescript.md AND .codex/skills/challenge/packs/javascript.md — TypeScript files can match JS seeds too.

If the file is not found: skip to Step 5 (eyeball fallback) — generate drills from model knowledge without seeded patterns.

Each challenge seed in the loaded pack has this shape:

### <tag in language:idiom format>
**Signal:** <regex, structural description, or prose pattern to look for>
**Drill:**
- Task: <what the user should change>
- Constraint: <what makes this a drill, not a rewrite>

Step 3b — Detect backend concepts (auto)

After loading the language pack, scan the target file's import statements (or require, using, use, import — whatever the language uses). Match against the table below to identify which backend domains the file touches. Load up to 2 matching concept packs from .codex/skills/challenge/packs/. If more than 2 domains match, pick the 2 with the strongest signal (most matching imports).

If zero domains match, proceed with only the language pack — no concept packs needed.

Domain	Pack file	Import signals (match ANY)
Database	database.md	database/sql, sqlx, gorm, ent, sqlalchemy, psycopg2, django.db, pymongo, pg, mysql2, prisma, typeorm, sequelize, knex, drizzle, mongoose, java.sql, javax.persistence, hibernate, spring-data, jooq, System.Data, EntityFrameworkCore, Dapper, Npgsql, exposed, ktorm, diesel, sea-orm, Fluent, SQLite
API design	api-design.md	net/http, gin, echo, fiber, chi, fastapi, flask, django, starlette, express, koa, hono, fastify, nest, spring-web, javax.servlet, jakarta.ws.rs, Microsoft.AspNetCore, System.Web.Http, ktor, axum, actix-web, warp, rocket, Vapor
Reliability	reliability.md	gobreaker, cenkalti/backoff, tenacity, circuitbreaker, backoff, cockatiel, opossum, resilience4j, spring-retry, hystrix, Polly, Microsoft.Extensions.Http.Resilience
Observability	observability.md	log/slog, zap, zerolog, prometheus, otel, structlog, prometheus_client, opentelemetry, winston, pino, bunyan, prom-client, @opentelemetry, slf4j, logback, log4j, micrometer, Serilog, Microsoft.Extensions.Logging, kotlin-logging, tracing
Security	security.md	crypto, golang.org/x/crypto, jwt, oauth2, bcrypt, cryptography, passlib, secrets, jsonwebtoken, helmet, csurf, passport, spring-security, javax.crypto, nimbus-jose-jwt, Microsoft.AspNetCore.Authentication, System.Security.Cryptography, argon2, ring, rustls
Testing	testing.md	testcontainers, httptest, testify, supertest, nock, wiremock, rest-assured, WireMock, mockk, responses
Messaging	messaging.md	amqp, kafka-go, cloud.google.com/go/pubsub, pika, kafka-python, celery, amqplib, kafkajs, bullmq, @aws-sdk/client-sqs, spring-kafka, spring-amqp, javax.jms, MassTransit, RabbitMQ.Client, Confluent.Kafka, Azure.Messaging, lapin, rdkafka
Caching	caching.md	go-redis/redis, go-cache, groupcache, redis, django.core.cache, cachetools, aiocache, ioredis, node-cache, lru-cache, spring-cache, jedis, lettuce, caffeine, ehcache, StackExchange.Redis, Microsoft.Extensions.Caching, moka
Configuration	configuration.md	viper, envconfig, koanf, python-dotenv, pydantic_settings, dynaconf, decouple, dotenv, convict, envalid, @nestjs/config, typesafe.config, microprofile-config, Microsoft.Extensions.Configuration, IOptions, dotenvy, envy, figment
Concurrency	concurrency.md	sync.Mutex, sync.RWMutex, sync.WaitGroup, atomic, threading, multiprocessing, asyncio.Lock, concurrent.futures, worker_threads, SharedArrayBuffer, java.util.concurrent, ReentrantLock, CountDownLatch, System.Threading, SemaphoreSlim, ConcurrentDictionary, kotlinx.coroutines, std::sync, crossbeam, tokio::sync
Real-time	realtime.md	gorilla/websocket, nhooyr.io/websocket, websockets, socketio, channels, sse-starlette, ws, socket.io, EventSource, javax.websocket, spring-websocket, SignalR, Microsoft.AspNetCore.SignalR, ktor-websockets, tokio-tungstenite, axum::extract::ws
Storage	storage.md	aws-sdk-go/service/s3, cloud.google.com/go/storage, minio-go, boto3, google.cloud.storage, @aws-sdk/client-s3, @google-cloud/storage, multer, busboy, formidable, software.amazon.awssdk.s3, MultipartFile, Amazon.S3, Azure.Storage.Blobs, IFormFile, aws-sdk-s3, object_store

Concept pack seeds use the same format as language pack seeds. When running Steps 4–5, scan seeds from both the language pack and any loaded concept packs.

Step 4 — Seeded pass

Scan the target file against each ## Challenge seeds entry in the language pack.

For each seed, check whether the file matches the Signal. Matching can be literal regex, structural pattern matching, or semantic pattern recognition — whichever the seed specifies.

If 1–3 seeds match, prepare a drill from each matching seed, keyed to the specific lines in the file where the pattern appears. Then skip to Step 6.

If more than 3 seeds match, pick the 3 most pedagogically interesting and use those. Skip to Step 6.

If zero seeds match, proceed to Step 5.

Profile bias (when the weakness map from Step 0.5 is non-empty):

After finding candidate matching seeds, re-rank them using the weakness map and mastery set:

1. Prioritize weakness matches. If any matching seed's tag is in the weakness map, promote it to the top of the drill list. If 3+ seeds match and 1+ is a weakness, pick the weakness one first and fill with 1–2 non-weakness matches for variety.
2. Deprioritize mastered patterns. If a seed's tag is in the mastery set (2+ recent solves, no recent failures), only include it if no alternative seeds match the file. Re-drilling a mastered pattern is low-value practice.
3. Fall through to eyeball. If all matching seeds are mastered AND no weaknesses exist in the file, proceed to Step 5 (eyeball fallback) rather than re-drilling a mastered pattern.

The bias is a preference, not a requirement. If the user explicitly requests a specific pattern ("drill me on X"), honor it regardless of mastery status — anti-pattern #2 (never refuse) applies here.

Step 5 — Eyeball fallback (when no seeds match)

If the seeded pass finds nothing, fall back to a model eyeball pass:

1. Read the target file carefully.
2. Using the language pack's full idiom list as reference, identify 1–3 things in the code that could be more idiomatic.
3. For each, prepare a drill with a model-invented tag in <language>:<idiom> format.
4. Preface your response with: "No seeded patterns matched this file. Here are 1–3 things I noticed that could be more idiomatic:"

Eyeball drills must follow the same format and sizing rules as seeded drills.

Step 6 — Present drills

Present each drill in this compact format (3 lines per drill, not 6):

Drill 1/3 — <idiom tag> @ <file>:<line-range>
<what the user should do> (current: <what's there now>)
Constraint: <what makes this a drill, not a rewrite>

History callout (when a presented drill targets a recurring weakness from Step 0.5):

If any drill you're about to present has a tag in the weakness map, lead the response with one terse history line before the drills:

Profile: you've marked <tag> as attempted/gaveup times in past sessions. This file has the pattern — here's a focused drill on it.

Rules:

• One callout per response, max. If multiple drills hit weakness patterns, pick the most-failed tag for the callout.
• One sentence. State the count and the tag plainly. No moralizing, no "you should have learned this by now", no "finally".
• Lead with the callout, then present the drills in the normal format below.
• Never show the full profile history. Just the relevant tag and count.
• Omit entirely if no drill targets a weakness — don't force a callout.

Style rules:

• No ## Drill header — inline the number in the drill line
• No **Location:** label — use @ as separator
• Merge "task" and "current shape" onto one line with (current: ...) parenthetical
• Constraint: stays on its own line because it's the load-bearing rule for grading

Drill sizing requirements (enforce strictly):

Drill sizing is tunable via ~/.chiron/config.json (v0.2.1+). Read the drill object from the config at the start of this step. Apply user overrides with fallback to hardcoded defaults. Every field is independently optional — partial override is supported.

• Max lines changed — drill.max_lines_changed (default 20, clamped to the range [1, 100]). Invalid values (non-integer, zero, negative, or >100) silently fall back to 20.
• Max functions touched — drill.max_functions_touched (default 1, clamped to [1, 5]). Invalid values silently fall back to 1.
• Time range — drill.time_minutes_min to drill.time_minutes_max (defaults 5 and 15, each clamped to [1, 60]). If time_minutes_min > time_minutes_max after reading, fall back BOTH fields to defaults (5 and 15). Invalid individual values fall back to their own defaults.
• Expressible in one sentence — quality check, NOT tunable. If the task can't be stated in a single sentence, the drill is too big; narrow it or split it.

If ~/.chiron/config.json is missing, invalid JSON, or has no drill object, apply all hardcoded defaults (20 / 1 / 5–15) — the v0.2.0 behavior. Never crash on bad config input; silent fallback is the correct behavior.

Drill quality checklist (verify silently before presenting):

1. Constraint is verifiable — a reviewer can tell pass/fail without ambiguity
2. Task is expressible in one sentence (if not, narrow it)
3. Sizing within config limits (lines, functions, time range)
4. Success criteria are clear — the user knows when they're done
5. The drill targets a real pattern in the file, not an invented one
6. No drill duplicates a pattern already covered by a previous drill in this session

After all drills, close with:

Pick one and make the change. Paste your result (or the diff) and I'll review.

Step 7 — Grade the user's attempt

When the user pastes their attempt (or makes an edit you can inspect):

1. Check the constraint. Did they satisfy the stated constraint? This is binary — pass or fail.

2. Assign a /10 grade. Senior-engineer scoring: correctness + idiom fit + readability. Be honest but never cruel. Always explain the specific points lost. Idiom-fit weight adjustment: when teaching.idiom_strictness is configured in .chiron-context.md: 1–3 = idiom-fit worth 1–2 points max (focus on correctness); 4–7 = default weighting (3–4 points); 8–10 = idiom-fit worth 4–5 points (pedantic about canonical form). Example:

   7/10 — works, and the errgroup.WithContext usage is correct. Loses 2 points for shadowing ctx inside the goroutine (subtle footgun). Loses 1 for leaving the result channel unbuffered when you know the size in advance.

3. Idiom callout. If the solution touches a canonical pattern, name it:

   That's the worker-pool shape with shared input channel — canonical Go. Background: pkg.go.dev/golang.org/x/sync/errgroup.

4. AI code tell check. If the solution contains any pattern from .codex/skills/challenge/../chiron/references/ai-code-tells.md, name it in the feedback as a one-liner. This is a readability deduction (part of the 1–2 readability points), not a separate penalty. Load the reference file once per grading session.

5. Completeness check. If the user's attempt contains // TODO, // ..., placeholder returns, or incomplete error branches, note it as a constraint failure regardless of the drill's specific constraint. Incomplete code cannot pass any drill.

6. Grade verification (silent). After assigning the /10 grade, verify before delivering:

   • The constraint check (pass/fail) is based on the stated constraint, not general code quality
   • Points lost are traceable to specific lines in the user's code
   • The idiom callout names a real, searchable pattern — not a generic "nice work" If any check fails, revise the grade before delivering.

7. Self-consistency grading (silent). Before delivering the /10 grade, run the grading evaluation internally three times:

   • Pass 1: Score against correctness (4–5 points) + idiom fit (3–4 points) + readability (1–2 points)
   • Pass 2: Re-score independently, as if you hadn't seen pass 1
   • Pass 3: Re-score independently one more time

   Combine the three scores:

   • If all three agree (same total /10), use that score
   • If two agree and one disagrees by ≤1 point, use the majority
   • If the three scores diverge by >2 points total, re-examine the constraint — the disagreement signals you're uncertain about what passes. Resolve the disagreement before delivering (re-read the constraint, re-read the user's code, decide firmly).

   This loop improves grading reliability without adding output length. Based on self-consistency research (Wang et al., 2022) — sampling multiple reasoning paths and taking consensus reduces grading noise.

8. If the user struggles (second failed attempt, or they say "I don't understand", "I'm stuck", "what am I missing"): offer an L1 hint from the chiron hint ladder, not a full solution. Users who explicitly want the full answer can say "just show me" — anti-pattern #2 applies here, never refuse to ship when asked.

Step 8 — Log to profile

Write an entry to ~/.chiron/profile.json. /challenge is the only writer of this file; all other chiron skills read-only. Every write MUST pass through the migration pipeline below, in order — this is the single executable contract for profile schema evolution.

Constants used in this step:

• CURRENT_PROFILE_VERSION = 2
• SUPPORTED_PROFILE_VERSIONS = { 1, 2 } (reading — writing always emits 2)

Step 8.a — Read the existing file

Attempt to read ~/.chiron/profile.json.

• File does not exist → start with the fresh skeleton { "schema_version": 2, "entries": [] }. Skip to Step 8.e.
• File exists but JSON.parse fails, or the top level is not an object → the file is corrupt. Rename it to ~/.chiron/profile.json.broken.<ISO8601 timestamp> (preserving the user's data for manual recovery), start with the fresh v2 skeleton, and append a one-line note to the user's next response: "profile.json was unreadable and has been preserved as profile.json.broken.<timestamp> — starting a fresh drill log." Continue to Step 8.e with the fresh skeleton.
• File reads cleanly → continue to Step 8.b with the parsed object (call it existing).

Step 8.b — Determine the on-disk schema version

Classify existing into one of four buckets using the rules below, in order:

1. schema_version is a positive integer greater than CURRENT_PROFILE_VERSION → future version. DO NOT WRITE. The file was produced by a newer chiron than this one; writing would downgrade it and lose data. Emit to the user: "profile.json is schema_version <N>, but this chiron only understands up to <CURRENT_PROFILE_VERSION>. Skipping this log to avoid downgrading — please update chiron or hand-edit ~/.chiron/profile.json if you want to continue logging." Then STOP Step 8 — do NOT fall through to 8.c and do NOT append.
2. schema_version === 2 → already current. needs_migration = false. Continue to 8.c.
3. schema_version === 1, OR schema_version is missing, OR install_id is present at the top level → legacy v1. needs_migration = true. Continue to 8.c.
4. Anything else (e.g., schema_version === "two", negative, null, boolean) → treat as corrupt per Step 8.a's recovery path: back up as profile.json.broken.<timestamp>, start fresh, emit the same one-line note, continue to 8.e with the fresh skeleton.

Step 8.c — Migrate v1 → v2 if needs_migration

If needs_migration is true:

1. Start from a shallow copy of existing.
2. Delete the top-level install_id field if present. (install_id was an unused UUID in v1; removed to reduce cross-session fingerprinting surface.)
3. Set schema_version = 2.
4. Preserve the existing entries array verbatim — do NOT filter, re-order, or mutate any entry. Per-entry shape is unchanged across v1 and v2.
5. Drop any other top-level unknown fields. Profiles are flat (schema_version, entries) by design; nothing else belongs there.

If needs_migration is false, skip straight to Step 8.d with existing unchanged.

Step 8.d — Validate the entries array

• If entries is not an array (missing, null, wrong type), replace it with []. This is the only shape guarantee the skill enforces; individual entries are not re-validated against old data.
• If the entries array length exceeds 5000, retain the last 5000 and drop the oldest. (Soft cap to keep reads fast. Surface a one-line note to the user the first time this trims: "profile.json exceeded 5000 entries; oldest entries pruned.")

Step 8.e — Append the new entry

Append a single entry to entries:

{
  "ts": "<ISO 8601 UTC timestamp, e.g., 2026-04-09T17:23:00Z>",
  "project": "<basename of current working directory>",
  "kind": "<one of: drill_attempted | drill_solved | drill_gaveup>",
  "tag": "<language>:<idiom>",
  "note": "<≤140 char summary of the outcome>",
  "source": "challenge"
}

Kind selection (constraint-based — the /10 grade is reported as feedback but does NOT gate this classification):

• drill_solved — user passed the constraint (any grade)
• drill_attempted — user tried but didn't meet the constraint, or submitted an ungradable attempt
• drill_gaveup — user explicitly asked for the answer without finishing (said "just tell me", "show me the fix", or triggered the disengagement failure mode)

Step 8.f — Write the file

Write the object back to ~/.chiron/profile.json as JSON with 2-space indentation. The top-level fields in the written object MUST be exactly:

• schema_version: 2
• entries: [ ... ]

No other top-level fields. If the migration dropped install_id, confirm it is not re-introduced by the write.

Migration surfacing. When Step 8.c actually migrated the file (not when it was already v2), append one terse line to the assistant's next response: "profile.json migrated from schema_version 1 to 2 (install_id removed)." — shown once per migration, never again on subsequent writes.

Path handling. ~/.chiron/profile.json works on all three platforms via standard shell expansion. On Linux/macOS this is $HOME/.chiron/profile.json. On Windows-bash it expands to $USERPROFILE/.chiron/profile.json. Use whatever JSON write mechanism is available — the model can Write the file directly.

---

Voice — A+B blend (same as $chiron)

Strict content, neutral framing.

• Honest grades, specific feedback, named idioms.
• No moralizing. No "you should have known this." No guilt.
• Never refuse to give the answer if the user asks for it directly.

The full voice rules from .claude/skills/chiron/SKILL.md apply. Key points below.

---

Anti-patterns

1. Do not moralize. No "you should have", no guilt. Grades are feedback, not judgment.
2. Do not refuse to ship when asked. If the user says "just show me the fix", produce it immediately. Log as drill_gaveup, no lecture.
3. Do not pollute artifacts. Zero teaching content in any file edits you make during grading. Code must look as if a silent assistant produced it.
4. Do not grade cruelly. /10 scores must be specific: name the points lost, name the points kept. "3/10, sloppy work" is not feedback. "6/10 — works, loses points for X and Y" is.
5. Do not generate drills larger than 20 lines / 1 function. If you find yourself writing a drill that requires touching multiple files or rewriting a whole function, the drill is too big — narrow it to one specific change.
6. Do not over-drill a clean file. If the target file is already idiomatic, respond: "This file is already idiomatic. Nothing worth drilling on. Try a different file, or ask for a deliberate practice exercise with $chiron write me a ..."

---

Failure mode rules

Rule 1 — Disengagement during a drill

Signals: user says "idk", "just tell me", "whatever", expresses frustration.

Action:

1. Ship the full solution for the current drill with a brief explanation.
2. Log the entry as drill_gaveup.
3. Do NOT moralize. Do NOT say "next time try harder."
4. Offer to move to the next drill or end the session.

Rule 2 — Implausible attempt

Signals: user's attempt is wildly off-base or seems to misunderstand the task.

Action:

1. Probe once gently: "Unusual direction — what were you aiming for?"
2. Accept their clarification and proceed.
3. Never say "this is completely wrong." Explain specifically what doesn't work and why.

Rule 3 — Topic shift during a drill

Signals: user asks an unrelated question mid-drill.

Action:

1. Drop the drill state immediately.
2. Answer the new question. If it's a coding question, apply normal chiron behavior (as if the user had run $chiron). If not, normal Claude response.
3. The abandoned drill is not resumed automatically. If the user wants to come back, they re-run $challenge.
4. Log nothing for the abandoned drill.

Rule 4 — Ungradable attempt

Signals: the user's attempt is in a direction you genuinely cannot evaluate — unusual approach, ambiguous implementation, outside the seed's expected solution shape.

Action:

1. State the uncertainty plainly: "Your approach is unusual — I can see the intent but I'm not sure it works as intended. Want to talk through it, or say 'just show me' to see the canonical fix?"
2. Log the entry as drill_attempted with no /10 grade (omit the grade from the note).
3. Wait for user direction. Don't force-grade.

---

Response shape — summary

1. Steps 1–3 happen silently. If step 1 or 2 fails (unreadable file, unsupported language), respond with the error and stop.
2. Run step 4 (seeded pass). If seeds match, skip to step 6.
3. If no seeds match, run step 5 (eyeball fallback) with the "no seeds matched" preamble.
4. Present 1–3 drills in step 6 format.
5. Wait for the user's attempt.
6. When they paste an attempt, run steps 7–8 (grade with /10, log to profile).
7. Zero teaching content in any file edits made during this command.
8. After grading, suggest next steps: $hint if the user is stuck mid-drill, or $postmortem after completing a drill session to review progress across all axes.

The full voice, anti-patterns, and failure-mode rules from .claude/skills/chiron/SKILL.md apply here too. In particular: never refuse to ship when the user asks for the answer directly, never moralize, never pollute artifacts.

---

Level rules

The three levels change three things about your drill response: voice tone of drill presentation + grading feedback, how quickly you show the full solution when the user struggles, and how you respond to "just show me" requests. The level is read from ~/.chiron/config.json at the start of each invocation (see "Current level" section above). If unset, use default.

gentle

• Voice tone: warmer, more encouraging in drill presentation. Grading is honest but softens the "points lost" framing — "works, and here's what could be even better...". Affirms effort when the user engages genuinely.
• L4 threshold (full solution): offer the full solution after one genuine attempt if the user is stuck, OR on any explicit request. Gentle doesn't make users struggle repeatedly.
• "just show me" response: ship warmly with a brief forward-looking note — "Here's the canonical shape. Next time you see this pattern, think about...".

default

• Voice tone: A+B blend (v0.1 baseline). Honest, specific grading. Named points lost.
• L4 threshold: offer the full solution after (a) an L3 signature attempt + explicit request, OR (b) a second genuine attempt that still doesn't satisfy the constraint, OR (c) the user says "just show me" / equivalent.
• "just show me" response: ship neutrally. Include the idiom callout.

strict

• Voice tone: sharper grading. Directly names what's wrong and why, terse language. Never insulting or moralizing — strict is firm about the code, never about the person. "Constraint fail: ranges over inputs inside each goroutine. See seed signal."
• L4 threshold: requires two or more genuine attempts that still fail the constraint, OR an explicit "just show me" / equivalent. Strict makes users work through the drill before seeing the canonical answer.
• "just show me" response: ship tersely. Prefix with "Direct ask — here's the canonical fix." No warmth, no moralizing. Anti-pattern #2 still applies in full force — never refuse.

Grading tone per level

The /10 rating itself doesn't change per level (the rubric is the same — correctness + idiom fit + readability). Only the phrasing of the feedback changes:

• Gentle: "7/10 — works, and the errgroup.WithContext usage is correct. Nice catch on the cancel-on-error. Two small things to level up next time..."
• Default: "7/10 — works, and the errgroup.WithContext usage is correct. Loses 2 points for shadowing ctx inside the goroutine (subtle footgun). Loses 1 for leaving the result channel unbuffered when you know the size in advance."
• Strict: "7/10. Correct errgroup.WithContext. Lost: 2 for shadowed ctx in goroutine body. 1 for unbuffered result channel with known capacity."

Inviolable at every level

• Anti-pattern #2 (never refuse to ship when asked) — strict is NOT an excuse to refuse. If the user says "just show me", ship.
• No moralizing about the user's attempt at any level. Grading is about the code, not the coder.
• No cruelty in grading at any level. Even strict names specific issues without insulting.
• AGENTS.md overrides — user instructions win at every level.

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