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/saitarrun/devforge-ai/token-efficiencynpx skills add saitarrun/Devforge-ai --skill token-efficiencygit clone --depth 1 https://github.com/saitarrun/Devforge-aiWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/saitarrun/devforge-ai/token-efficiency)<a href="https://agentmods.dev/skills/saitarrun/devforge-ai/token-efficiency"><img src="https://agentmods.dev/badge/skills/saitarrun/devforge-ai/token-efficiency.svg" alt="Measured on agentmods" height="20"></a>What 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 | $0.00026 | $0.00657 |
| Opus 5 | $0.00013 | $0.00329 |
| Sonnet 5 | $0.00005 | $0.00131 |
| Haiku 4.5 | $0.00003 | $0.00066 |
Grade A, and why
token-efficiency 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 yesterday.
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 — 62 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Token Efficiency & Precision Engineering Skill
This skill enforces strict token conservation, prevents context-window bloat, and optimizes model invocation costs while maximizing code generation and diagnostic accuracy.
1. Token Conservation Hierarchy
When analyzing large codebases or executing multi-agent pipelines, follow the Token Conservation Hierarchy:
[Level 1: Semantic AST Query (Lowest Token Cost: ~50-200 Tokens)]
↳ Query code-review-graph or symbol definitions; avoid loading full files.
↓
[Level 2: Targeted Line-Range Slice (Minimal Cost: ~200-500 Tokens)]
↳ Read only the specific target function / interface lines (StartLine to EndLine).
↓
[Level 3: Compact Handoff Artifacts (Bounded Cost: ~500-1,500 Tokens)]
↳ Never pass entire conversation logs forward; distill decisions into clean markdown handoffs.
↓
[Level 4: Full File Reads (Cautious / Restricted: >2,000 Tokens)]
↳ Read entire files only when strictly required for syntax validation. Never read binary or vendor files.
2. The 5 Rules of High-Precision Token Economy
Rule 1: Zero Redundant File Dumps
- Never re-read files already present in memory or referenced by previous steps.
- Prefer targeted inspection: fetch only the exact 30–50 lines of an implementation seam rather than the entire 2,000-line module.
Rule 2: Handoff State Compaction
- At every phase boundary (
Plan -> Build -> Verify -> Ship -> Operate), write a structured summary tohandoffs/<phase>-handoff.md. - Downstream agents only read the handoff file, resetting conversation token depth back to zero and avoiding exponential context degradation.
Rule 3: Structural Search Over Greedy Grep
- Do not run unconstrained recursive text searches that dump thousands of matched lines into the context window.
- Filter queries with file extensions and directory boundaries (e.g.
apps/claims-engine/src/**/*.ts).
Rule 4: Compact Diff Chunks on Edits
- When modifying code, use targeted line replacements rather than rewriting entire files.
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.
- yesterday First seen · 62 lines · 26 tokens per session scan A f1e43c4bd318
token-efficiency is a skill published in the GitHub repository saitarrun/Devforge-ai (5 stars, last pushed 22d ago), licensed Apache-2.0. It adds 26 tokens to every session and 657 once invoked, about $0.0001 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 2026-09-03.
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