/ijfw-compute
Use when the user says: 'compute', 'crunch this', 'analyze logs', 'aggregate the data', 'run a script', 'dedupe', 'count by', 'top N', or any data-shaping ask. Replaces dumping raw data into context with sandboxed script execution.
$ npx -y skills add FerroxLabs/ijfw --skill ijfw-compute --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/ijfw-compute
Context preview
The summary Claude sees to decide when to auto-load this skill.
Use when the user says: 'compute', 'crunch this', 'analyze logs', 'aggregate the data', 'run a script', 'dedupe', 'count by', 'top N', or any data-shaping ask. Replaces dumping raw data into context with sandboxed script execution.
SKILL.md
ijfw-compute.SKILL.mdname: ijfw-compute
description: "Use when the user says: 'compute', 'crunch this', 'analyze logs', 'aggregate the data', 'run a script', 'dedupe', 'count by', 'top N', or any data-shaping ask. Replaces dumping raw data into context with sandboxed script execution."
context: fork
model: sonnet
Compute over read. When data is large or repetitive, run a sandboxed script and surface only the result. The four trees below decide which lever to pull.
Compute tree -- run a sandboxed script
Use when the input is bigger than the answer: log files, CSV/JSON dumps, file-tree walks, repeated string transforms, aggregate stats, deduping. Call `ijfw_run compute:python "<script>"` for pandas / numpy / stdlib parsing. Call `ijfw_run compute:js "<script>"` for JSON shape-checks, regex sweeps, quick numeric work. Sandbox is allowlist filesystem (cwd + project root) + best-effort OS-level network deny; opt-in with `IJFW_COMPUTE_NET=1` if the script needs egress. Default timeout 30s, hard cap 300s via `IJFW_COMPUTE_TIMEOUT_MS`. Output cap 100MB; overflow lands in the on-disk log.
Example: a 40MB nginx log. Instead of reading 200k lines into context, run `ijfw_run compute:python "import collections,sys;c=collections.Counter();[c.update([l.split()[8]]) for l in open('access.log')];print(c.most_common(10))"` and surface the top-10 status-code summary.
Read tree -- skip compute, just read
Use when the file is small (<2k lines), the task is a code edit or config tweak, or the agent needs to reason about structure rather than aggregate content. Direct Read is cheaper than spinning a subprocess; compute has fixed startup overhead.
Example: editing a single function in `mcp-server/src/server.js`. Read the file, edit it, move on. No compute call needed.
Index tree -- write findings to FTS5 for later search
Use after a compute or research step produces a finding worth recalling across sessions. Call `ijfw_run index:source <kind> <body>` to write into the per-project FTS5 db at `<project>/.ijfw/index/compute.db`. Schema is `raw` table (source_kind, source, session_id, project_root, body, ts). Per-write `PRAGMA quick_check` guards integrity.
Citation provenance (C9.6): pass `--source=<pointer>` before the body to attach an origin (file path / observation kind / skill name). Search hits surface this pointer + the session_id so users can trace where each row came from. Omitted -> source stays NULL.
Example: after analyzing the nginx log, index the verdict: `ijfw_run index:source compute_output --source=logs/access.log "Top error 502 from upstream X 2026-05-08; 4.1% of requests"`. Next session can search for it via the search tree below.
Search tree -- query the existing index
Use before computing again. If a previous session already answered a similar question, recall it instead of recomputing. Call `ijfw_memory_search compute:query "<query>"` for top-k FTS5 hits scoped to the current project. Each hit returns body + source_kind + source + session_id + ts; the agent decides whether the cached finding is still fresh and can cite the source pointer.
Stemmed BM25 (C9.4): the FTS5 tokenizer is `porter unicode61`. Morphological variants collapse: "authenticate" / "authenticating" / "authentication" share a stem; "configure" / "configured" / "configuring" share a stem.
Synonym expansion (C9.5): default-on. Bare tokens expand against ~80 coding- domain pairs (db <-> database, auth <-> authentication, perf <-> performance, etc.). The result envelope reports `synonym_matches: { token: [expansions] }` so callers see what fired. Disable per-process via `IJFW_SYNONYM_EXPAND=0`.
Session filter (C9.6): append `--session=<id>` to a query to scope hits to a single session. The envelope echoes the filter as `session_filter`.
Example: user asks "what was the top nginx error last week?" Run `ijfw_memory_search compute:query "nginx error rate"` first; if a recent indexed finding lands, surface it directly. If empty or stale, fall back to the compute tree on fresh log data.
Rules
- Default to compute when input >> output. Default to read when input <= output.
- Always index actionable findings; don't index raw dumps.
- Always search before computing on a recurring question.
- Subprocess runs are sandboxed -- treat untrusted script bodies as
untrusted; never disable the sandbox to make a script work.
- One compute-nudge per session via the PreToolUse hook; further nudges
are suppressed.
Read more
name: ijfw-compute description: "Use when the user says: 'compute', 'crunch this', 'analyze logs', 'aggregate the data', 'run a script', 'dedupe', 'count by', 'top N', or any data-shaping ask. Replaces dumping raw data into context with sandboxed script execution." context: fork model: sonnet
Compute over read. When data is large or repetitive, run a sandboxed script and surface only the result. The four trees below decide which lever to pull.
Compute tree -- run a sandboxed script
Use when the input is bigger than the answer: log files, CSV/JSON dumps, file-tree walks, repeated string transforms, aggregate stats, deduping. Call `ijfw_run compute:python "<script>"` for pandas / numpy / stdlib parsing. Call `ijfw_run compute:js "<script>"` for JSON shape-checks, regex sweeps, quick numeric work. Sandbox is allowlist filesystem (cwd + project root) + best-effort OS-level network deny; opt-in with `IJFW_COMPUTE_NET=1` if the script needs egress. Default timeout 30s, hard cap 300s via `IJFW_COMPUTE_TIMEOUT_MS`. Output cap 100MB; overflow lands in the on-disk log.
Example: a 40MB nginx log. Instead of reading 200k lines into context, run `ijfw_run compute:python "import collections,sys;c=collections.Counter();[c.update([l.split()[8]]) for l in open('access.log')];print(c.most_common(10))"` and surface the top-10 status-code summary.
Read tree -- skip compute, just read
Use when the file is small (<2k lines), the task is a code edit or config tweak, or the agent needs to reason about structure rather than aggregate content. Direct Read is cheaper than spinning a subprocess; compute has fixed startup overhead.
Example: editing a single function in `mcp-server/src/server.js`. Read the file, edit it, move on. No compute call needed.
Index tree -- write findings to FTS5 for later search
Use after a compute or research step produces a finding worth recalling across sessions. Call `ijfw_run index:source <kind> <body>` to write into the per-project FTS5 db at `<project>/.ijfw/index/compute.db`. Schema is `raw` table (source_kind, source, session_id, project_root, body, ts). Per-write `PRAGMA quick_check` guards integrity.
Citation provenance (C9.6): pass `--source=<pointer>` before the body to attach an origin (file path / observation kind / skill name). Search hits surface this pointer + the session_id so users can trace where each row came from. Omitted -> source stays NULL.
Example: after analyzing the nginx log, index the verdict: `ijfw_run index:source compute_output --source=logs/access.log "Top error 502 from upstream X 2026-05-08; 4.1% of requests"`. Next session can search for it via the search tree below.
Search tree -- query the existing index
Use before computing again. If a previous session already answered a similar question, recall it instead of recomputing. Call `ijfw_memory_search compute:query "<query>"` for top-k FTS5 hits scoped to the current project. Each hit returns body + source_kind + source + session_id + ts; the agent decides whether the cached finding is still fresh and can cite the source pointer.
Stemmed BM25 (C9.4): the FTS5 tokenizer is `porter unicode61`. Morphological variants collapse: "authenticate" / "authenticating" / "authentication" share a stem; "configure" / "configured" / "configuring" share a stem.
Synonym expansion (C9.5): default-on. Bare tokens expand against ~80 coding- domain pairs (db <-> database, auth <-> authentication, perf <-> performance, etc.). The result envelope reports `synonym_matches: { token: [expansions] }` so callers see what fired. Disable per-process via `IJFW_SYNONYM_EXPAND=0`.
Session filter (C9.6): append `--session=<id>` to a query to scope hits to a single session. The envelope echoes the filter as `session_filter`.
Example: user asks "what was the top nginx error last week?" Run `ijfw_memory_search compute:query "nginx error rate"` first; if a recent indexed finding lands, surface it directly. If empty or stale, fall back to the compute tree on fresh log data.
Rules
- Default to compute when input >> output. Default to read when input <= output.
- Always index actionable findings; don't index raw dumps.
- Always search before computing on a recurring question.
- Subprocess runs are sandboxed -- treat untrusted script bodies as
untrusted; never disable the sandbox to make a script work.
- One compute-nudge per session via the PreToolUse hook; further nudges
are suppressed.
IJFW — It Just F*cking Works. Ferrox Labs' local-first infrastructure for AI coding agents: shared memory, smart routing, multi-AI cross-audits, disciplined workflow.
Repo: FerroxLabs/ijfw
Other skills on ijfw.
- /ijfw-agents-md
Maintain canonical AGENTS.md (open spec). Trigger: 'agents.md', 'update AGENTS.md', or auto-fired by ijfw-team after agent generation.
Open skill - /ijfw-auto-memorize
Session-end auto-extraction of lessons, errors, fixes, and user feedback into structured memory. Fires at session end. Requires consent on first run.
Open skill - /ijfw-commit
Terse conventional commits. Trigger: commit, git commit, /ijfw-commit
Open skill - /ijfw-complete-milestone
Use when a milestone is shipping and you need to archive its artifacts, generate a summary, and seed the next milestone. Trigger: 'milestone complete', 'ship milestone', 'wrap milestone', 'complete milestone <id>', /ijfw-complete-milestone.
Open skill - /ijfw-compress
Compress memory/context files into terse form. Trigger: /compress, compress file
Open skill - /ijfw-core
IJFW efficiency layer -- smart output, routing, context discipline. Always active. Trigger: any IJFW interaction. Disable: 'ijfw off' or 'normal'.
Open skill