savethetokens
0
总安装量
3
周安装量
安装命令
npx skills add https://github.com/redclawww/savethetokens --skill savethetokens
Agent 安装分布
amp
3
opencode
3
kimi-cli
3
codex
3
github-copilot
3
claude-code
3
Skill 文档
Context Governor
Optimize context usage with practical, high-impact workflows and scripts.
Non-Negotiable Guardrails
- Keep scope locked to the user request. Do not add extra features, pages, or telemetry unless asked.
- Treat token optimization as a constraint, not the goal. Correctness and security win over token reduction.
- Never claim token savings without before/after measurement on comparable tasks.
- If context-saving actions risk quality loss, keep the extra context and state the tradeoff.
- Never reduce code thoroughness to save tokens. Tests, strict config, safety checks, and error handling are non-negotiable. Save tokens from message verbosity â never from output completeness.
Operating Modes
Lean Mode(default): Use lightweight context hygiene only; do not create new benchmark artifacts.Measurement Mode: Use launch-readiness or A/B telemetry scripts only when user asks for proof/percentages.
Claude Code Message Budget (required)
- Keep progress updates short and phase-based. Do not narrate every file write.
- Do not paste long command output unless user asks. Summarize only key signals.
- Do not repeat the same command without a code/input change; if retried, state the reason once.
- If
/contextshows message growth is unusually high, switch to stricter concise mode:- fewer updates
- shorter summaries
- batch related edits before reporting
- Prefer one concise final summary over long running commentary.
- For benchmark runs, enforce matched behavior on both variants:
- same stop criteria
- same compact policy
- same output style (no extra giant report in one variant only)
Operating Playbook
- Confirm objective and lock scope in one sentence.
- Keep one chat session per task. Start a new session for unrelated work.
- Use
! <command>for direct shell commands when no reasoning is required. - Run
/contextperiodically. Compact around 50% usage instead of waiting for hard limits. - Before
/compactor/clear, create a checkpoint file with next steps and touched files. - Keep top-level docs lean; move deep details to linked
docs/*.md. - Before final output on code tasks, run the quality gates in
docs/QUALITY_GATES.md. - For token-savings claims, run matched A/B using
docs/BENCHMARK_PROTOCOL.md. - For Claude benchmark runs, use
docs/STRICT_BENCHMARK_PROMPT.mdas the session starter.
Quick Commands
# Generate execution plan
python ~/.claude/skills/savethetokens/scripts/govern.py --budget 8000
# Generate checkpoint before compact/clear
python ~/.claude/skills/savethetokens/scripts/session_checkpoint.py \
--task "..." \
--done "..." \
--next "..." \
--context-percent 52 \
--message-count 36
# Create session hook (Claude Code)
python ~/.claude/skills/savethetokens/scripts/session_hook_generator.py --project .
# Optimize CLAUDE.md
python ~/.claude/skills/savethetokens/scripts/claude_md_optimizer.py --analyze
# Calculate cost savings
python ~/.claude/skills/savethetokens/scripts/cost_calculator.py --developers 5
# Run launch-readiness benchmark with section-wise savings
python ~/.claude/skills/savethetokens/scripts/launch_readiness.py
# Run live A/B telemetry session (auto split control/optimized)
python ~/.claude/skills/savethetokens/scripts/govern.py \
--input context.json \
--budget 8000 \
--experiment-id claude-launch-v1 \
--variant auto \
--assignment-key TICKET-123
# Generate measured A/B report from live sessions
python ~/.claude/skills/savethetokens/scripts/ab_telemetry.py \
--experiment-id claude-launch-v1 \
--days 14 \
--required-intents code_generation,debugging,planning,review \
--min-samples-per-intent 5
# Strict mode: exit 2 if claim gates fail (CI-friendly)
python ~/.claude/skills/savethetokens/scripts/ab_telemetry.py \
--experiment-id claude-launch-v1 \
--strict-claim-mode
# Print report JSON to stdout (pipe to jq, etc.)
python ~/.claude/skills/savethetokens/scripts/ab_telemetry.py \
--experiment-id claude-launch-v1 \
--json-stdout
# Code-task quality gate checklist (required before final answer)
cat ~/.claude/skills/savethetokens/docs/QUALITY_GATES.md
# Compare two /context snapshots (control vs optimized)
python ~/.claude/skills/savethetokens/scripts/context_snapshot_diff.py \
--before-file before.txt \
--after-file after.txt \
--strict
# Compact watchdog (advisory, safe defaults)
python ~/.claude/skills/savethetokens/scripts/compact_watchdog.py \
--context-file context_snapshot.txt \
--require-checkpoint
# Dynamic tool filtering (fail-open recommended)
python ~/.claude/skills/savethetokens/scripts/tool_filter.py \
--input tools.json \
--query "..." \
--fail-open
# Semantic skill selection (recommendation only)
python ~/.claude/skills/savethetokens/scripts/skill_selector.py \
--query "..."
# External memory store (bounded retrieval)
python ~/.claude/skills/savethetokens/scripts/memory_store.py search \
--query "..." \
--for-prompt \
--top-k 5 \
--max-chars 1200
# Print lean session prompt template
cat ~/.claude/skills/savethetokens/docs/LEAN_SESSION_PROMPT.md
# Print strict benchmark harness prompt
cat ~/.claude/skills/savethetokens/docs/STRICT_BENCHMARK_PROMPT.md
Scripts
| Script | Purpose |
|---|---|
govern.py |
Main entry – execution plans |
analyze.py |
Context analysis |
prune.py |
Prune to budget (max 40%) |
session_hook_generator.py |
Session-start hooks |
session_checkpoint.py |
Save compact-ready session checkpoints |
claude_md_optimizer.py |
Optimize CLAUDE.md |
quick_ref_generator.py |
Generate QUICK_REF.md |
tiered_context.py |
3-tier context classification |
relevance_scorer.py |
Score context relevance |
cost_calculator.py |
ROI tracking |
launch_readiness.py |
Launch benchmark + section-wise savings report |
ab_telemetry.py |
Live A/B telemetry report with confidence checks |
context_snapshot_diff.py |
Detect token regressions from /context snapshots |
compact_watchdog.py |
Safe advisory for /compact and /clear decisions |
tool_filter.py |
Dynamic tool filtering with fail-open safeguards |
skill_selector.py |
Semantic skill ranking with confidence gating |
memory_store.py |
External memory store with bounded retrieval |
path_filter.py |
Filter package dirs |
Quality Rules
- NEVER prune system prompts, errors, recent messages
- Max pruning: 40% (keeps quality)
- When uncertain â KEEP content
- Will exceed budget rather than harm quality
- Keep solution minimal and request-aligned; avoid speculative architecture
- Run relevant tests/checks for touched areas, or explicitly state what could not be run
Completeness Checklist (never skip under token pressure)
Token savings come from shorter messages and smarter context â never from cutting corners on output quality. Before finalizing any code task, verify:
- Strict config â Enable strictest compiler/linter settings available (e.g.
"strict": truein tsconfig). Zeroanytypes, zero@ts-ignore, zero@ts-nocheck. - Tests for touched code â Every changed function/module has corresponding tests. Minimum: one happy path, one error path per public function.
- Safety limits â Runtime code that loops, recurses, or processes unbounded input must have explicit guards (max iterations, call depth, step limits, timeouts).
- Error handling with context â Errors include location info (file, line, span) and actionable messages. No bare
catch(e) {}orexcept Exception: pass. - Input validation at boundaries â Validate user input, API responses, and file I/O. Internal code can trust internal types.
- Security basics â No command injection, no unsanitized template interpolation, no hardcoded secrets. Parameterize queries.
- Build passes â Run type-check/compile/build before declaring done. If it can’t be run, state why.
- State what was not verified â If any check above could not be performed (no test runner, no build script), explicitly list it in the final summary.
Where to save tokens instead: shorter progress updates, batch related edits, omit command output unless asked, compact at 50% context.
Detailed Docs (read on-demand)
- EXECUTION_PLANS.md – Plan structure
- PRUNING_STRATEGIES.md – Pruning logic
- MODEL_SELECTION.md – Model recommendations
- TOKEN_ESTIMATION.md – Token counting
- SESSION_PLAYBOOK.md – Practical compact/reset workflow
- QUALITY_GATES.md – Mandatory code-quality and claim-quality gates
- BENCHMARK_PROTOCOL.md – Matched A/B process for fair measurement
- LEAN_SESSION_PROMPT.md – Paste-ready strict token-discipline prompt
- STRICT_BENCHMARK_PROMPT.md – Paste-ready harness for fair Claude Code A/B testing
- ADVANCED_AUTOMATION.md – Optional advanced features with safety controls
- LAUNCH_READINESS.md – Measured launch benchmark report
- LIVE_TELEMETRY.md – Live control vs optimized experiment report