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.
git clone --depth 1 https://github.com/sifxprime/kodelyth-eccWrote 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/commands/sifxprime/kodelyth-ecc/terse)<a href="https://agentmods.dev/commands/sifxprime/kodelyth-ecc/terse"><img src="https://agentmods.dev/badge/commands/sifxprime/kodelyth-ecc/terse/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/sifxprime/kodelyth-ecc/terse"><img src="https://agentmods.dev/badge/commands/sifxprime/kodelyth-ecc/terse.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00031 | $0.00352 |
| Opus 5.5 | $0.00012 | $0.00141 |
| Sonnet 5.5 | $0.00006 | $0.00070 |
| Haiku 4.5 | $0.00003 | $0.00035 |
Grade A, and why
terse 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 1mo 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.
What it actually says
/terse — output compression
Activate the terse-mode skill and set its dial.
Usage
/terse— set tofull(default)/terse lite— light trim/terse full— telegram-style fragments/terse ultra— maximum compression/terse off— restore normal voice
Instructions to the assistant
Read the arguments passed to this command. Set the terse-mode level:
- If args are empty → use
full - If args are one of
lite / full / ultra / off→ use that - Any other value → answer briefly with the valid options and do not change the level
For the rest of this session (until /terse off or a new /terse <level>):
- Load the rules from
skills/terse-mode/SKILL.md - Apply the level's compression rules to every reply
- Preserve byte-exact: code blocks, inline code, shell commands, error text, URLs, paths, identifiers, numbers, versions
- Never translate — keep the user's language
- Never compress memory captures, tool outputs, or file contents
Confirm activation in one line:
terse: <level> — code and commands preserved byte-exact
Then answer whatever the user asks — in the new voice.
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.
- 1mo ago First seen · 41 lines · 31 tokens per session scan A 31e4072a7afd
terse is a command published in the GitHub repository sifxprime/kodelyth-ecc (11 stars, last pushed 14d ago), licensed MIT. It adds 31 tokens to every session and 352 once invoked, about $0.0001 per session on Opus 5.5. 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.
Other commands, from other repositories
episode
Write an episode checkpoint receipt for the current session's episode.
review-agent-config
Diagnostic gate that checks CLAUDE.md and AGENTS.md for completeness, consistency, and stale artifacts — run right after /cold-start and before /add-feature. Read-only; produces a findings report.
session-info
Copy project path, session title, and session ID to clipboard (no LLM round-trip).
cold-start
Bootstrap the ai/guide maps and diagrams (the cold-start pass). Drafts everything as [inferred] for a human to audit.
create-feature-catalog
Deep-mine the source code to discover implemented features; writes ai/analysis/FEATURECATALOG.md.
fix-bug
Fix a bug using the knowledge layer — reproduce first, failing regression test, root cause, surgical fix, review and ledger entry after.