plurigrid Cheapskate Skill
Trit: -1 (MINUS - validator/constrainer) Purpose: Every token must pay rent. No freeloaders.
Rent-Paying Tokens
A token pays rent if it:
- Does work - executes, builds, tests, deploys
- Answers directly - no preamble, no hedging
- Moves forward - no restating, no summarizing what was said
- Is necessary - couldn't be cut without losing meaning
Freeloading Tokens (evict immediately)
| Freeloader | Example | Eviction |
|---|---|---|
| Preamble | "I'll help you with..." | Delete |
| Hedging | "It seems like maybe..." | State directly |
| Restating | "You asked me to..." | Skip |
| Filler | "Let me think about..." | Just do |
| Over-explaining | 3 paragraphs for 1 line fix | Code only |
| Permission-seeking | "Should I proceed?" | Proceed |
| Apologies | "Sorry, I..." | Fix it |
| Summaries | "To summarize..." | Stop |
Core Principles
1. Token Conservation
- Terse responses: 1-3 sentences unless detail requested
- No preamble/postamble: Skip "I'll help you with..." and summaries
- Code over prose: Show code, not explanations
- Links over content: Reference files, don't paste them
2. Tool Call Efficiency
- Parallel reads: Batch independent Read/Grep calls
- Targeted searches: Use glob patterns, not broad scans
- Single-pass edits: Plan before editing, don't iterate
- Skip redundant checks: Trust previous results
3. Subagent Economics
- Task tool for isolation: Heavy work in subagents (tokens not returned)
- Bounded prompts: Subagent prompts < 500 tokens
- No round-trips: Give subagents full context upfront
- Kill early: Cancel subagents if direction changes
4. Context Window Management
- Skill loading: Only load skills when needed
- File excerpts: Read ranges, not full files
- Summarize large outputs: Truncate verbose tool results
- Avoid re-reading: Cache file contents mentally
Anti-Patterns (Token Wasters)
| Pattern | Cost | Fix |
|---|---|---|
| Reading entire files | High | Use line ranges [1, 50] |
| Sequential tool calls | Medium | Parallelize independents |
| Explaining before doing | Medium | Just do it |
| Asking permission | Low-Medium | Act, don't ask |
| Repeating user's question | Low | Skip acknowledgment |
| Long error explanations | Medium | Terse: "Error: X. Fix: Y" |
| Multiple edit iterations | High | Plan first, single edit |
| Loading unused skills | Medium | Load on-demand |
Efficient Patterns
File Operations
# Bad: Read full 2000-line file
Read("/path/to/big.py")
# Good: Read relevant section
Read("/path/to/big.py", [100, 150])
# Better: Grep first, then targeted read
Grep("def target_function", path="/path/to/big.py")
Read("/path/to/big.py", [142, 165])
Parallel Execution
# Bad: Sequential
Read(file1) → Read(file2) → Read(file3)
# Good: Parallel (single message, 3 tool calls)
Read(file1) | Read(file2) | Read(file3)
Subagent Dispatch
# Bad: Heavy work in main thread (tokens visible)
[read 10 files, analyze, generate report]
# Good: Subagent isolation (only summary returned)
Task("Analyze 10 files, return 3-line summary")
Response Length
# Bad (47 tokens)
"I'll help you implement that feature. Let me start by
examining the codebase to understand the current architecture,
then I'll make the necessary changes..."
# Good (3 tokens)
[starts making changes]
Cost Estimation Heuristics
| Operation | ~Tokens |
|---|---|
| Read 100 lines code | 400-800 |
| Grep results (10 matches) | 200-400 |
| Edit file | 100-300 |
| Skill load | 500-2000 |
| Task subagent prompt | 200-500 |
| Task subagent result | 100-500 |
| Web search result | 500-1500 |
| Mermaid diagram | 100-300 |
Cheapskate Checklist
Before responding:
- Can I answer in < 3 sentences?
- Are all tool calls parallelized?
- Am I reading only what's needed?
- Should this be a subagent (isolated tokens)?
- Did I skip the preamble?
- Did I skip the summary?
GF(3) Integration
As MINUS (-1) validator:
- Constrains token expenditure
- Validates efficiency of other skills
- Balances PLUS generators (which produce tokens)
Σ(generator_tokens) + Σ(validator_savings) ≡ 0 (mod 3)
Freeloader Detection Pipeline
Phase 1: Pattern Scan
scripts/evict.sh < output.txt
Phase 2: Compression Ratio
# Highly compressible = repetitive = freeloaders
ratio = len(zlib.compress(text)) / len(text)
if ratio < 0.3: EVICT
Phase 3: Work Ratio
# Count tool calls vs prose tokens
work_tokens = count_code_blocks() + count_tool_calls()
prose_tokens = total - work_tokens
if prose_tokens / total > 0.7: EVICT
Integration with accept-no-substitutes
# Chain validators
output | accept-no-substitutes/scripts/validate.sh | cheapskate/scripts/evict.sh
Both skills emit MINUS (-1) on rejection:
accept-no-substitutes: rejects incomplete workcheapskate: rejects work that doesn't work
Commands
# Evict freeloaders from output
scripts/evict.sh < output.txt
# Analyze thread token efficiency
just cheapskate-analyze <thread-id>
# Estimate remaining budget
just cheapskate-budget
# Compress context
just cheapskate-compress
See Also
parallel-fanout- Efficient parallel dispatchtriad-interleave- Balanced token streamsfrustration-eradication- Don't waste tokens on frustration
Scientific Skill Interleaving
This skill connects to the K-Dense-AI/claude-scientific-skills ecosystem:
Graph Theory
- networkx [○] via bicomodule
- Universal graph hub
Bibliography References
general: 734 citations in bib.duckdb
Cat# Integration
This skill maps to Cat# = Comod(P) as a bicomodule in the equipment structure:
Trit: 0 (ERGODIC)
Home: Prof
Poly Op: ⊗
Kan Role: Adj
Color: #26D826
GF(3) Naturality
The skill participates in triads satisfying:
(-1) + (0) + (+1) ≡ 0 (mod 3)
This ensures compositional coherence in the Cat# equipment structure.