Borrowing it
Nothing to install: this file belongs to sopaco/cowork-forge. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/sopaco/cowork-forge/main/.agents/skills/terrain-knowledge-skill/SKILL.mdgit clone --depth 1 https://github.com/sopaco/cowork-forgeWrote 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/sopaco/cowork-forge/terrain-knowledge-skill)<a href="https://agentmods.dev/skills/sopaco/cowork-forge/terrain-knowledge-skill"><img src="https://agentmods.dev/badge/skills/sopaco/cowork-forge/terrain-knowledge-skill.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
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 5.1 | $0.00036 | $0.00905 |
| Opus 5 | $0.00018 | $0.00452 |
| Sonnet 5 | $0.00007 | $0.00181 |
| Haiku 4.5 | $0.00004 | $0.00090 |
Grade A, and why
terrain-knowledge-skill 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 8d 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 — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Terrain Knowledge Skill
Terrain stores AI knowledge assets under .terrain/ in this repository (not a global ~/.terrain/knowledge directory). The desktop app registry at ~/.terrain/registry.json only maps slugs → repo paths.
Load rtk-skill when you need to run shell commands during investigation (git, grep repomix file, tests). Resolve tools via conventional paths (~/.terrain/bin/…) with bunx/npx fallback — see rtk-skill / codegraph-skill.
Knowledge layers (mandatory order)
-
Architecture —
.terrain/agent/context.md- Module map, core flows, system boundaries, tech stack
- Check
.terrain/agent/context-meta.jsonormeta.jsonfor asset timestamps - Read directly (short); no RTK needed
-
Private domain —
.terrain/knowledge/**/*.md- Business glossary, internal frameworks, APIs, scaffolding guides
- Team-maintained markdown; read in filename sort order when surveying
-
Structured meta —
.terrain/agent/meta-inputs.md- Compiled from
terrain-meta.jsonandknowledge/scans
- Compiled from
-
Source index — see
repomix-context-skill- Local
.terrain/agent/repomix.md(gitignored; regenerate via Terrain scan)
- Local
Knowledge freshness (mandatory before architecture answers)
Before trusting context.md for module/architecture questions:
~/.terrain/bin/terrain tools freshness --project <slug>
# or: bunx @terrain-ai/cli tools freshness --project <slug>
This recomputes when stale and writes .terrain/.meta/freshness.json. Do not only read that JSON statically — it is a local cache snapshot.
| Score | Rule |
|---|---|
< 50 |
Do not rely on macro context; use repomix-context-skill |
50–69 |
Cross-check with repomix grep or codegraph-skill |
≥ 70 |
Architecture context is generally reliable |
On conflict: repomix source slices > codegraph > agent/context.md > human/
For symbol impact/callers, also see codegraph-skill (CodeGraph status can lie; use terrain tools codegraph-drift).
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.
- 8d ago First seen · 91 lines · 36 tokens per session scan A 7f90bb535b36
terrain-knowledge-skill is a skill published in the GitHub repository sopaco/cowork-forge (92 stars, last pushed 13d ago), licensed MIT. It adds 36 tokens to every session and 905 once invoked, about $0.0002 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 2026-08-30.
Other skills, from other repositories
wiki
LLM Wiki — persistent markdown knowledge base that compounds across sessions (Karpathy model).
remember
Review reusable project knowledge and decide what belongs in project memory, notepad, or durable docs.
memory
Persistent, token-efficient project memory. When ON, maintains a .shob/memory/ folder of structured .md files so the full context of the project is NEVER lost across responses, sessions, or context compaction. Uses progressive disclosure — routes through a lightweight INDEX and loads only the files a task needs…
deja-search
Search deja before re-deriving past work: when the user refers to earlier sessions or decisions, before debugging an error, and before implementing something that may already exist. It searches this machine's own history across every AI coding tool used on it, going back further than deja itself was installed.
general
Handle everyday conversation, answer questions, manage files, take notes, run scripts, and maintain persistent memory across sessions. Use when the user asks a general question, requests file operations, wants to brainstorm ideas, needs to-do tracking, asks you to remember something, or requests skill search and…
deja-history
Search the user's past AI coding sessions. Use when they say things like 'didn't we fix this before', 'what did we decide about X', or before re-debugging an error that may already be solved.