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/baokhang83/fluencyloop/featurenpx skills add baokhang83/fluencyloop --skill featuregit clone --depth 1 https://github.com/baokhang83/fluencyloopWhat 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 | $0.00140 | $0.11146 |
| Opus 5 | $0.00070 | $0.05573 |
| Sonnet 5 | $0.00028 | $0.02229 |
| Haiku 4.5 | $0.00014 | $0.01115 |
Grade B, and why
feature scanned grade B with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Strips warnings and disclaimersmediumAnti-refusal
Omitting safety caveats hides risk from the user and is a common jailbreak preamble.
each slice boundary. Never gate; never lecture. Keep the developer the author. How it starts
The opening of the file, as written. The whole thing — 683 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/fluencyloop:feature — declare a feature, build it fluent
This is the contributor's entry point. A feature is a branch (feature/<slug>); it owns
its design reasoning and session journals. You will: (1) declare the feature, (2) frame its
concepts and relationships, (3) build it in slices — teaching and journaling one or two real decisions at
each slice boundary. Never gate; never lecture. Keep the developer the author.
Bundled CLI (Claude Code)
Before invoking a deterministic command, use this plugin's bundled launcher:
"${CLAUDE_PLUGIN_ROOT}/bin/fluencyloop" <arguments>. Every fluencyloop … command below
means that exact Bash-tool command; it is never a chat instruction or a globally installed
command.
Do not hand-scaffold .fluencyloop/, .claude/skills/, designs, sessions, state, or helper
scripts. The bundled CLI creates the deterministic files and returns their paths.
Local site — open once
Before the first user-visible response, invoke
"${CLAUDE_PLUGIN_ROOT}/bin/fluencyloop" site --ensure --open-once --json. This ensures the
reader for every workflow entry, but opens a browser tab only once while that managed reader is
alive. If it reports running: true and no earlier assistant message in this session starts with
FluencyLoop site:, say FluencyLoop site: <url> (opened in browser). once, using its returned
URL. Do not mention an unavailable site or repeat the announcement.
Generated prose — ASD-STE100
Write generated user-facing technical prose in ASD-STE100 style: use short, direct sentences, active voice, one main action per sentence, and stable, unambiguous terms. Preserve product names, code identifiers, CLI commands, field names, and exact recorded values. Do not claim formal ASD-STE100 compliance: that requires checking the official controlled dictionary and rules. Apply this style to live decision-boundary teaching as well as generated Markdown and PR prose. It makes the required explanation clearer; it does not shorten, skip, or replace that explanation.
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 · 683 lines · 140 tokens per session scan B c901d788c593
feature is a skill published in the GitHub repository baokhang83/fluencyloop (44 stars, last pushed 16d ago), licensed Apache-2.0. It adds 140 tokens to every session and 11,146 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it B with 1 finding (strips warnings and disclaimers). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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