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/ph3on1x/wisci/selectnpx skills add ph3on1x/wisci --skill selectgit clone --depth 1 https://github.com/ph3on1x/wisciWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/ph3on1x/wisci/select)<a href="https://agentmods.dev/skills/ph3on1x/wisci/select"><img src="https://agentmods.dev/badge/skills/ph3on1x/wisci/select.svg" alt="Measured on agentmods" height="20"></a>What 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 | $0.00062 | $0.00737 |
| Opus 5 | $0.00031 | $0.00368 |
| Sonnet 5 | $0.00012 | $0.00147 |
| Haiku 4.5 | $0.00006 | $0.00074 |
Grade A, and why
select scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 61 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/select — Context Loader
Load exactly the context the current task needs. Every stored file is validated by staleness detection before it enters the window — outdated content is stripped, never loaded.
Store state
!python3 "${CLAUDE_PLUGIN_ROOT}/scripts/wisci.py" scan
If the scan above shows an error or an unexpanded variable, run the bundled script manually: it is at scripts/wisci.py relative to this skill's directory. Run
python3 <that path> scanwith Bash.
The scan classifies every file in .wisci/ (fresh / stale / broken), lists what changed, and enumerates handoff streams. Trust it — do not re-derive staleness with your own git commands.
Mode Detection
Check $ARGUMENTS:
- Empty or blank: execute bare mode — read and follow references/bare-mode.md
- Has content: execute targeted mode — read and follow references/targeted-mode.md
Staleness Action Rules
Apply to every context file before loading:
- Fresh: load as-is.
- Stale: load with stale sections stripped. A section "depends on" a reference if that reference's path appears in the section body.
- Strip sections whose dependent references appear in the scan's
changedlist. - If a changed reference appears only in
## Referencesand in no section body, strip nothing — prepend instead:> **Note:** Referenced file <path> has changed since this context was written. - When sections are stripped, prepend:
> **Note:** N sections stripped — their referenced files changed. Consider /write <topic> to refresh.
- Strip sections whose dependent references appear in the scan's
- Broken: do not load. Report: " references code that no longer exists. Delete it or refresh with /write."
- Handoff leaves older than 7 days (scan
age_days): warn before loading — "handoff is N days old; its next steps may be outdated." - Files without a
## Referencesmanifest have no trackable references — treat as fresh.
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 3d ago First seen · 61 lines · 62 tokens per session scan A 3cfa0436049d
select is a skill published in the GitHub repository ph3on1x/wisci (1 stars, last pushed 1mo ago), licensed MIT. It adds 62 tokens to every session and 737 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
contorium-workspace-memory
Use Contorium workspace memory layers (focus, session events, Git, export) when resuming AI work or avoiding repeated project explanation.
neo4j-agent-memory-skill
Authoritative reference for the neo4j-agent-memory Python package — a graph-native memory system for AI agents built on Neo4j — and for the hosted service (NAMS) at memory.neo4jlabs.com. Use this skill whenever the user mentions neo4j-agent-memory, agent memory with Neo4j, context graphs, the POLE+O model…
neo4j-gds-skill
Neo4j Graph Data Science (GDS) embedded plugin via Python client or Cypher — covers GraphDataScience, gds.v2 plugin endpoints, gds.version, native projection, Cypher projection, graph catalog operations, stream/stats/mutate/write modes, memory estimation, PageRank, Louvain, WCC, FastRP, KNN, Node Similarity, ML…
build-personal-brain
Create, resume, validate, connect, or maintain a private cross-project memory for AI assistants. Use when a person asks to build a personal memory from local work folders and past assistant conversations, continue an interrupted memory audit, connect an existing memory to another local assistant, verify that the…
ox-consult
Search SageOx team memory BEFORE answering from first-principles reasoning. Auto-fire when the user references recent or specific work or asks a before/after question: "I just pushed...", "did X fix Y?", "is the alert gone now?", "this request", or anything tied to a prior decision, a prod anomaly, or a metric/cost…
dev-wrapup
Review the current session for learnings and self-improvement signals. Surfaces memory candidates and improvement opportunities for user-confirmed application. Use after completing work to review the session for learnings and improvement signals.