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Compress-Cache-Retrieve huge repetitive array tool output before it hits context: keep a sample, cache the rest, leave a hash.
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基于 SOC 职业分类
Compress-Cache-Retrieve for huge, repetitive array tool output (logs, scan results, time series, event streams) before it enters context. Keeps an informative sample — endpoints, anomalies/change-points, head/tail — drops the redundant rest to a local cache, and leaves a retrievable hash. Use when a tool returns a long uniform JSON array you must read but mostly skim, and the full set is one command away if needed. Lossy-but-recoverable.
Write less code and say less about it: YAGNI, stdlib-first, terse prose. Cuts agent token cost on every coding and writing task.
Write less code and say less about it. Applies YAGNI and stdlib/native-first so the agent writes the minimum code that needs to exist, and responds tersely — stripping filler, hedging, and pleasantries while keeping code, identifiers, and technical terms exact. Use whenever writing, modifying, refactoring, reviewing, or explaining code, or any response where output volume drives token cost — even if the user never says "minimal" or "concise". Especially in agentic coding, where the volume of generated code and prose runs up the bill.
Honey for plain Claude — the terse-prose core with no agent-harness features. Paste into a claude.ai Project's custom instructions, a Style, or an API system prompt. Strips filler, hedging, and pleasantries from every response while keeping facts, names, numbers, steps, and code exact. No tools required.
Read huge dense read-only text as PNG pages via pxpipe export: ~60-75% fewer input tokens. Lossy on exact strings; never for files you will edit.
Read huge, dense, read-only text as rendered PNG pages instead of raw text — image tokens scale with pixels, not characters, so token-dense bulk (big files, vendored code, diffs, logs) costs ~60–75% less as an image. Use when you must skim or reason over thousands of lines you will NOT edit or byte-copy. Lossy on exact strings: never for files you'll Edit, secrets, hashes, or byte-exact values. Fable-class readers only.
| name | honey-ccr |
| description | Compress-Cache-Retrieve huge repetitive array tool output before it hits context: keep a sample, cache the rest, leave a hash. |
| homepage | https://github.com/Green-PT/honey-for-devs |
| license | MIT |
The cheapest token is the one not sent. A 500-row log read for one error line costs 500 rows of context. CCR keeps the rows that carry signal and caches the rest — recoverable by hash, so nothing is lost.
Borrowed from headroom's SmartCrusher. Lossy by design — only for data you
skim, never for payloads where every row matters (e.g. a code-review handoff
where the implementer needs all findings; use eson encode losslessly there).
tool-that-spews-json | eson crush # → sampled view + sentinel; originals cached
eson retrieve <hash> # → the full original array, verbatim
crush prints the kept sample plus a sentinel
{"_ccr":"<<ccr:HASH N_rows_offloaded>>"}. When you need a dropped row, read the
hash from the sentinel and run eson retrieve <hash>.
.honey-ccr/ (override with HONEY_CCR_DIR).crush returns the array unchanged with no sentinel — safe to pipe anything.While Honey is active, a registered PostToolUse hook applies this automatically to
Bash output — no opt-in per call. Big uniform JSON arrays (≥20 items, ≥2k chars) are
crushed; repetitive text (≥25 lines) gets consecutive repeats collapsed to ⟨×N⟩.
The original is always stashed first, and the rewritten result ends with the exact
eson retrieve <hash> command that restores it. /honey off disables the hook;
history already in context is immutable — this fires at entry, the only place a
hook can act.
Caveat: Claude Code builds affected by anthropics/claude-code#68951 ignore the
hook's Bash rewrite, making it inert (a session-start warning tells you when this
applies). Manual some-tool | eson crush piping is unaffected — prefer it there.