Context Compression
guanyang/open-agent-hub
This skill should be used when long-running agent sessions need context compression, structured summarization, compaction, token-per-task optimization, or durable handoff summaries that preserve…
Standardized cost-estimation framework for greatcto plans. An agent skill from avelikiy/great_cto.
Install Cost Model
$ npx skills add avelikiy/great_cto --skill cost-model -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install avelikiy/great_cto cost-model --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/avelikiy/great_cto.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/cost-model .claude/skills/cost-model && rm -rf skills-srcUse ~/.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/
Install the "cost-model" agent skill from https://github.com/avelikiy/great_cto/tree/main/skills/cost-model into .claude/skills/cost-model/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cost-model", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/avelikiy/great_cto/tree/main/skills/cost-modelType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add avelikiy/great_cto --skill cost-model -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install avelikiy/great_cto cost-model --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/avelikiy/great_cto.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/cost-model .agents/skills/cost-model && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "cost-model" agent skill from https://github.com/avelikiy/great_cto/tree/main/skills/cost-model into .agents/skills/cost-model/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cost-model", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add avelikiy/great_cto --skill cost-model -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install avelikiy/great_cto cost-model --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/avelikiy/great_cto.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/cost-model .cursor/skills/cost-model && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "cost-model" agent skill from https://github.com/avelikiy/great_cto/tree/main/skills/cost-model into .cursor/skills/cost-model/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cost-model", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/avelikiy/great_cto.git --path skills/cost-model--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add avelikiy/great_cto --skill cost-model -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install avelikiy/great_cto cost-model --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/avelikiy/great_cto.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/cost-model .gemini/skills/cost-model && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "cost-model" agent skill from https://github.com/avelikiy/great_cto/tree/main/skills/cost-model into .gemini/skills/cost-model/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cost-model", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install avelikiy/great_cto cost-modelInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add avelikiy/great_cto --skill cost-model -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/avelikiy/great_cto.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/cost-model .github/skills/cost-model && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "cost-model" agent skill from https://github.com/avelikiy/great_cto/tree/main/skills/cost-model into .github/skills/cost-model/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cost-model", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add avelikiy/great_cto --skill cost-model -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install avelikiy/great_cto cost-model --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/avelikiy/great_cto.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/cost-model .opencode/skills/cost-model && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "cost-model" agent skill from https://github.com/avelikiy/great_cto/tree/main/skills/cost-model into .opencode/skills/cost-model/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cost-model", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
cost-model- GitHub stars
- 102
- Token cost
- ~1.3k tokens
- SKILL.md length
- 476 words
- Files
- 1
- Skills in repo
- 27
- Repo updated
- First seen
- Licence
- MIT
At a glance
Standardized cost-estimation framework for greatcto plans. An agent skill from avelikiy/great_cto.
- Tasks that involve LLM cost and token optimization
- SKILL.md covers The 4-line cost section, How to estimate each line, Sanity check before writing and Cost gates, plus 2 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Cost Model is an agent skill from avelikiy/great_cto. Standardized cost-estimation framework for greatcto plans. Forces explicit LLM cost, infra cost, human-supervision time, and the (defensible) human-equivalent comparison. Output format is parsable by the board's /api/cost path — must follow exactly.
Its SKILL.md is about 1.3k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in AI & LLM Engineering, covering LLM cost and token optimization. The repository describes itself as: You already have the agent. This is everything around it. greatcto runs Claude Code as a pipeline of 70 specialist agents — an independent model checks each stage before the next… The licence is MIT.
When your agent uses it
- Tasks that involve LLM cost and token optimization
Example prompts
- “/cost-model”
Requirements
- Pre-approved tools (allowed-tools): Read, Write
What it can do on your machine
Read from SKILL.md and the folder at commit 97dd037. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves these tools, so the agent can use them without asking each time:
ReadWrite
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).
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
Cost Model loads about 1.3k tokens when it runs. Until then it costs about 65 tokens; SKILL.md has 476 words of instructions outside code blocks.
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 avelikiy/great_cto at commit 97dd037, republished under its MIT licence (© avelikiy). 476 words, ~1,275 tokens.
Download SKILL.mdSave it as
.claude/skills/cost-model/SKILL.md (or your agent's skills folder).- name
- cost-model
- description
- Standardized cost-estimation framework for great_cto plans. Forces explicit LLM cost, infra cost, human-supervision time, and the (defensible) human-equivalent comparison. Output format is parsable by the board's /api/cost path — must follow exactly.
- allowed-tools
- Read, Write
- when_to_use
- Apply when: - pm is writing PLAN-*.md and the Cost section is required - architect is forecasting LLM burn for a new feature (gate:cost for AI archetypes)…
- effort
- low
- paths
- docs/plans/**, docs/architecture/**
Cost model — make cost claims defensible
great_cto reports cost numbers on the board. Those numbers MUST be auditable, because a wrong "7,638×" claim killed credibility (see docs/blog/cost-dashboard-rebuild.md). This skill defines the format.
The 4-line cost section
Every PLAN-.md and ARCH-.md cost section follows this exact template:
## Cost estimate
**LLM**: $<low>–<high> (<N> calls × $<per-call avg>)
**Human equiv**: $<low>–<high> (<hours> × $<rate>/h)
**Infra delta**: $<low>–<high>/month
**Time to ship**: <hours> agent-time, <hours> wall-clock
> Methodology: <one-sentence rationale for each range>Why this exact format?
The board's getCostHistory() parser anchors on line-start "LLM" and
"Human" labels. Mid-line references are ignored to prevent the
$240-trap regression. Stick to the template.
How to estimate each line
LLM cost
For each agent in the pipeline, estimate:
- Prompt tokens = (system prompt size) + (context the agent receives)
- Completion tokens = (typical output for that agent type)
Quick reference for Sonnet 4 ($3/M in, $15/M out):
| Agent | Typical prompt | Typical output | Per-call cost |
|---|---|---|---|
| architect | 14k | 1.5k | ~$0.06 |
| pm | 6k | 0.6k | ~$0.03 |
| senior-dev | 8k | 0.8k | ~$0.04 |
| qa-engineer | 11k | 0.5k | ~$0.04 |
| reviewer (avg) | 8-12k | 0.6k | ~$0.04 |
| security-officer | 12k | 1k | ~$0.05 |
| devops | 9k | 0.8k | ~$0.04 |
For Haiku ($0.80/M / $4/M), divide by ~4. For Opus 4 ($15/M / $75/M), multiply by ~5.
Sum across the pipeline stages that actually fire (use gatesFor() and
reviewersFor() from archetypes.ts to know the count).
Human equiv
The human cost to do the SAME work without agents. This is the "if I hired a senior engineer, how long would this task take, at what rate?"
- Senior engineer: $120-180/hour (mid-market US/EU)
- Staff engineer / specialist: $200-300/hour
- Domain expert (security, compliance): $250-400/hour
Estimate hours conservatively. A "small feature" the LLM does in 15 minutes might take a human 2-4 hours (it's never just the typing).
Infra delta
Only count what's NEW. If the feature adds a Redis instance, count Redis. If it adds 10MB/month of S3 storage, that's noise — don't list.
Show full SKILL.md (200 more words)Show less
Time to ship
Two numbers — both useful:
- Agent-time: wall-clock of LLM calls (typically 5-30 min)
- Wall-clock: actual elapsed including human gates (typically hours to days)
Sanity check before writing
Before committing the section to the plan, verify:
ratio = human_equiv / llm_costIf ratio > 1000, something is wrong. Common bugs:
| Bug | How to detect | Fix |
|---|---|---|
| Wrong unit ($ vs ¢) | LLM cost ends in /M tokens not $ | Convert: tokens / 1M × price |
| Counting savings not spend | "Human time saved" not "Human cost" | Use cost of doing it, not value of skipping |
| Mid-line label pollution | Plan has "$X LLM | $Y human" on one line |
| Forecast vs actual mixed | LLM forecast counts toward total_llm | Separate forecast section if needed |
Cost gates
For AI archetypes (mlops, ai-system, agent-product), the pipeline
opens gate:cost after architect's forecast. CTO must approve the
projected monthly burn before senior-dev starts.
Use the GATE template:
## Gate:cost forecast
| Production volume | Monthly LLM cost |
|---|---|
| 1K req/day | $X |
| 10K req/day | $Y |
| 100K req/day | $Z |
Recommended monthly cap: $<cap>
Triggers above cap: <what alerts fire, who gets paged>Anti-patterns
❌ Round-number theatre. "$0.50 LLM | $7,500 human" — looks suspicious. Use realistic ranges: "$0.50–1.20 | $225–360".
❌ Single point estimates. Always provide a range. Single numbers hide uncertainty.
❌ No methodology line. Just numbers without rationale is unverifiable.
❌ Hand-waved infra. "Some hosting cost" is not a number. Either give $, or say "infra: no change."
Example — good
## Cost estimate
**LLM**: $0.75–1.85 (3 tasks × $0.25–0.62 per Sonnet call)
**Human equiv**: $225–300 (1.5–2h × $150/h, mid-market senior)
**Infra delta**: $0/month (uses existing Express + Postgres)
**Time to ship**: ~15min agent-time, ~3h wall-clock (1 human gate)
> Methodology: tasks sized by line-count estimate; per-call cost from
> historical Sonnet 4 averages on this archetype's plans.Ratio = 300/1.85 = 162×. Plausible. Defensible.
© avelikiy, 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 skills/cost-model of avelikiy/great_cto.
Open the folder on GitHubat commit 97dd037
Compare with similar skills
Cost Model 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Cost Model this skillavelikiy/great_cto | 102 | — | ~1.3k | Automated safety check: Pass | MIT | |
| Context Compressionguanyang/open-agent-hub | 977 | 2 repos | ~4.6k | Automated safety check: Pass | MIT | |
| Bounty Hunter1sadjlk/bounty-hunter-skill | 282 | 1 repos | ~761 | Automated safety check: Pass | MIT | |
| Skill Shortenerluongnv89/asm | 954 | — | ~3.8k | Automated safety check: Notes | MIT | |
| Fleet Auditoralexgreensh/token-optimizer | 2.5k | — | ~1.7k | Automated safety check: Pass | Custom licence | |
| Context Auditundefined-ui/second-brain-os | 1k | — | ~802 | Automated safety check: Pass | MIT |
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Skill Shortener
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Refactor a too-long SKILL.md by progressive disclosure: measure token cost, classify every section KEEP/CUT/MOVE, shorten the body into references/ and scripts/, verify nothing was lost.
Fleet Auditor
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Cross-system agent token/cost audit (Claude Code, Codex, OpenClaw, Hermes, OpenCode): idle burns, model misrouting, config bloat, with dollar savings.
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Related
Categories
Questions about Cost Model
What does Cost Model do?
Standardized cost-estimation framework for greatcto plans. An agent skill from avelikiy/great_cto. Cost Model is an agent skill from avelikiy/great_cto. Standardized cost-estimation framework for greatcto plans.
When should I use Cost Model?
Cost Model fits situations like: tasks that involve LLM cost and token optimization.
How do I install Cost Model in Claude Code?
Run `npx skills add avelikiy/great_cto --skill cost-model -a claude-code`. Or copy the skill folder (skills/cost-model in avelikiy/great_cto) into .claude/skills/cost-model in your project. Claude Code loads it when a task matches its description.
How do I install Cost Model in Codex?
Run `npx skills add avelikiy/great_cto --skill cost-model -a codex`. Or copy the skill folder (skills/cost-model in avelikiy/great_cto) into .agents/skills/cost-model in your project. Codex loads it when a task matches its description.
Can I use Cost Model 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 avelikiy/great_cto --skill cost-model -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/cost-model, .gemini/skills/cost-model, .github/skills/cost-model and .opencode/skills/cost-model in your project.
What does Cost Model need to run?
SKILL.md names no scripts, command-line tools or credentials: Cost Model is instructions for the agent only. Its frontmatter pre-approves these tools: Read, Write.
Does Cost Model 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 Cost Model 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 Cost Model use?
Cost Model 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 Cost Model use?
About 1.3k tokens (SKILL.md is roughly 5.1k 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 Cost Model?
Skills that share tags, products or a category with Cost Model: Context Compression (guanyang/open-agent-hub, 977 stars), Bounty Hunter (1sadjlk/bounty-hunter-skill, 282 stars), Skill Shortener (luongnv89/asm, 954 stars) and Fleet Auditor (alexgreensh/token-optimizer, 2.5k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Cost Model?
avelikiy (a GitHub user) maintains it in avelikiy/great_cto, which has 102 GitHub stars. The repository holds 27 skills in this directory. The repository was last updated on October 9, 2026.
Source: avelikiy/great_cto on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.