Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/edimuj/tokenlean/add-featurenpx skills add edimuj/tokenlean --skill add-featuregit clone --depth 1 https://github.com/edimuj/tokenleanWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00051 | $0.00598 |
| Opus 5 | $0.00026 | $0.00299 |
| Sonnet 5 | $0.00010 | $0.00120 |
| Haiku 4.5 | $0.00005 | $0.00060 |
Grade A, and why
add-feature scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Add Feature
Add functionality by understanding existing code before writing new code.
Workflow
Locate → Understand → Implement → Integrate → Verify
1. Locate
Find where the feature belongs:
tl parallel "tl structure" "tl entry" "tl example <pattern>"
2. Understand
Before writing a single line:
tl parallel \
"symbols=tl symbols <file>" \
"style=tl style" \
"deps=tl deps <file>" \
"exports=tl exports <file>"
3. Implement
# Extending an existing file?
tl snippet <function> <file> # Read just the function you're modifying
# New file?
# Follow conventions from tl style, place per tl structure
# Adding a dependency?
tl npm <package> # Check size, health, and download stats first
4. Integrate
Wire it into the existing system:
tl parallel \
"impact=tl impact <modified-file>" \
"guard=tl guard" \
"diff=tl diff --breaking"
5. Verify
tl parallel "test=tl run '<test command>'" "testmap=tl test-map <file>"
Decision tree
Feature request → Does similar functionality exist?
├─ Yes (extending) → tl example to find the pattern
│ → tl symbols on target file
│ → tl snippet on the function to extend
│ → Implement following the existing pattern
├─ Yes (replacing) → tl impact on what you're replacing
│ → tl exports to check public API surface
│ → Implement, update all consumers
└─ No (greenfield) → tl structure for placement
→ tl style for conventions
→ tl entry to understand how it'll be wired in
→ Implement, then tl guard to check integration
Tips
- Always run
tl examplebefore implementing — the codebase almost always has a precedent - Use
tl npmbefore adding any new dependency — check size and health - Run
tl diff --breakingafter modifying any file with exports - For React/frontend projects, also use
tl componenton main UI files - If a file is under 150 lines, just read it directly — tokenlean overhead isn't worth it
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 91 lines · 51 tokens per session scan A b7a30c3b1c49
add-feature is a skill published in the GitHub repository edimuj/tokenlean (11 stars, last pushed 1mo ago), licensed MIT. It adds 51 tokens to every session and 598 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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