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Agent skill

Ijfw Compute

by FerroxLabs in FerroxLabs/ijfw

A skill your agent uses 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.

MITAuto-check passed

Install Ijfw Compute

skills CLI
$ npx skills add FerroxLabs/ijfw --skill ijfw-compute -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install FerroxLabs/ijfw ijfw-compute --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/FerroxLabs/ijfw.git skills-src && mkdir -p .claude/skills && cp -r skills-src/claude/skills/ijfw-compute .claude/skills/ijfw-compute && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
ijfw-compute
GitHub stars
212
Token cost
~1.1k tokens
SKILL.md length
571 words
Files
1
Skills in repo
38
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses 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.

  • The user says: compute
  • SKILL.md covers Compute tree -- run a…, Read tree -- skip compute,…, Index tree -- write findings… and Search tree -- query the…, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • Aggregate the data

What it does

Ijfw Compute is an agent skill from FerroxLabs/ijfw. 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.

Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

The repository describes itself as: IJFW — It Just Fcking Works. Ferrox Labs' local-first infrastructure for AI coding agents: shared memory, smart routing, multi-AI cross-audits, disciplined workflow. The licence is MIT.

When your agent uses it

  • The user says: compute
  • Aggregate the data
  • Any data-shaping ask

Example prompts

  • “compute”
  • “crunch this”
  • “analyze logs”
  • “/ijfw-compute”

Requirements

  • Python 3

What it can do on your machine

Read from SKILL.md and the folder at commit eda62f3. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Ijfw Compute loads about 1.1k tokens when it runs. Until then it costs about 61 tokens; SKILL.md has 571 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~61
When it runs · the whole SKILL.md, loaded when a task matches
~1.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from FerroxLabs/ijfw at commit eda62f3, republished under its MIT licence (© FerroxLabs). 571 words, ~1,115 tokens.

Download SKILL.mdSave it as .claude/skills/ijfw-compute/SKILL.md (or your agent's skills folder).
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.

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.

Show full SKILL.md (243 more words)Show less

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.

© FerroxLabs, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in claude/skills/ijfw-compute of FerroxLabs/ijfw.

Open the folder on GitHubat commit eda62f3

Compare with similar skills

Ijfw Compute next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Ijfw Compute compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Ijfw Compute this skillFerroxLabs/ijfw212—~1.1kAutomated safety check: PassMIT
Ito Computeaffaan-m/ECC276k1 repos~1.7kAutomated safety check: PassMIT
Growth Logaffaan-m/ECC276k1 repos~1.7kAutomated safety check: PassMIT
Clickhouse Logs Queriessupabase/supabase111k—~2.4kAutomated safety check: PassApache-2.0
Investigating LogsPostHog/posthog40k—~2.1kAutomated safety check: PassCustom licence
Senior Computer Visiondavila7/claude-code-templates32k2 repos~1.4kAutomated safety check: PassMIT

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Questions about Ijfw Compute

What does Ijfw Compute do?

A skill your agent uses 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. Ijfw Compute is an agent skill from FerroxLabs/ijfw. 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.

When should I use Ijfw Compute?

Ijfw Compute fits situations like: the user says: compute; aggregate the data; any data-shaping ask.

How do I install Ijfw Compute in Claude Code?

Run `npx skills add FerroxLabs/ijfw --skill ijfw-compute -a claude-code`. Or copy the skill folder (claude/skills/ijfw-compute in FerroxLabs/ijfw) into .claude/skills/ijfw-compute in your project. Claude Code loads it when a task matches its description.

How do I install Ijfw Compute in Codex?

Run `npx skills add FerroxLabs/ijfw --skill ijfw-compute -a codex`. Or copy the skill folder (claude/skills/ijfw-compute in FerroxLabs/ijfw) into .agents/skills/ijfw-compute in your project. Codex loads it when a task matches its description.

Can I use Ijfw Compute in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add FerroxLabs/ijfw --skill ijfw-compute -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ijfw-compute, .gemini/skills/ijfw-compute, .github/skills/ijfw-compute and .opencode/skills/ijfw-compute in your project.

What does Ijfw Compute need to run?

SKILL.md names no scripts, command-line tools or credentials: Ijfw Compute is instructions for the agent only. Our summary lists: Python 3.

Does Ijfw Compute access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Ijfw Compute safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Ijfw Compute use?

Ijfw Compute is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Ijfw Compute use?

About 1.1k tokens (SKILL.md is roughly 4.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Ijfw Compute?

Skills that share tags, products or a category with Ijfw Compute: Ito Compute (affaan-m/ECC, 276k stars), Growth Log (affaan-m/ECC, 276k stars), Clickhouse Logs Queries (supabase/supabase, 111k stars) and Investigating Logs (PostHog/posthog, 40k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Ijfw Compute?

FerroxLabs (a GitHub user) maintains it in FerroxLabs/ijfw, which has 212 GitHub stars. The repository holds 38 skills in this directory. The repository was last updated on October 5, 2026.

Source: FerroxLabs/ijfw on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.