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Retrieve semantically relevant past learnings and analysis outputs using the csm CLI (HDC encoder with hybrid BM25 retrieval)
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| name | memory-context |
| description | Retrieve semantically relevant past learnings and analysis outputs using the csm CLI (HDC encoder with hybrid BM25 retrieval) |
| version | 1.0 |
Retrieve semantically relevant past learnings, analysis outputs, and project knowledge using the csm (Chaotic Semantic Memory) CLI.
cargo install chaotic_semantic_memory --bin csm
The skill checks for csm availability and auto-installs if missing.
If csm is not found, install automatically:
if ! command -v csm &> /dev/null; then
echo "Installing csm CLI..."
cargo install chaotic_semantic_memory --bin csm
# Verify installation
csm --version
fi
analysis/ or agents-docs/# Index lessons (lessons.jsonl stores lesson summary text in "title")
csm index-jsonl -F agents-docs/lessons.jsonl --field title --id-field id --tag-field tags
# Index analysis outputs and docs
csm index-dir --glob "analysis/**/*.md" --glob "agents-docs/*.md" --heading-level 2
Index stored in .git/memory-index/csm.db (per-clone, never committed).
# Natural language query (default: hybrid retrieval)
csm query "how to handle git worktree cleanup" --top-k 5
# Code identifier query (exact match optimized)
csm query "MAX_CONTEXT_TOKENS" --top-k 3 --output-format json
# Code-heavy query
csm query "get_user_by_id" --code-aware --top-k 5
--output-format table (default): human-readable--output-format json: machine-parseable for agent consumption--output-format quiet: IDs onlyUse a hard post-query cap from .agents/config.sh:
source .agents/config.sh
csm query "how to handle git worktree cleanup" --top-k 8 --output-format table |
awk -v max_tokens="$MAX_CONTEXT_TOKENS" '
{
for (i = 1; i <= NF; i++) {
if (token_count < max_tokens) {
printf "%s%s", $i, (token_count + 1 < max_tokens ? " " : "\n")
token_count++
} else {
exit
}
}
}
'
This enforces an approximate token ceiling even if retrieval output is verbose.