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 skills add shyftlabs/continuum --skill continuum-agentgit clone --depth 1 https://github.com/shyftlabs/continuumWrote 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/shyftlabs/continuum/continuum-agent)<a href="https://agentmods.dev/skills/shyftlabs/continuum/continuum-agent"><img src="https://agentmods.dev/badge/skills/shyftlabs/continuum/continuum-agent/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/shyftlabs/continuum/continuum-agent"><img src="https://agentmods.dev/badge/skills/shyftlabs/continuum/continuum-agent.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Output Handling · line 30 Output size or generation rate is not bounded. Unbounded output enables denial-of-service through resource exhaustion, log flooding, or context-window stuffing.Fix: Set explicit limits on output length, generation count, and rate. Use max_tokens and truncation to prevent unbounded output.
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 | $0.00074 | $0.01287 |
| Opus 5.5 | $0.00030 | $0.00515 |
| Sonnet 5.5 | $0.00015 | $0.00257 |
| Haiku 4.5 | $0.00007 | $0.00129 |
Grade A, and why
continuum-agent 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 1mo 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 — 152 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Continuum Agent Skill
Authoritative source: docs/agent.md.
Core API
from continuum.agent import BaseAgent, AgentRunner
from continuum.agent.config import AgentConfig, AgentMemoryConfig, RunnerConfig
from continuum.agent.types import (
Handoff, MemoryScope, RunContext, AgentResponse, EventType,
)
Minimal agent
agent = BaseAgent(
name="my-agent", # required, [A-Za-z0-9_-]+
instructions="...", # supports {slot} templates
model="gpt-4o-mini", # provider chosen by prefix
temperature=0.7,
max_tokens=None,
)
runner = AgentRunner()
resp = await runner.run(agent, "user input", user_id="u1", session_id="s1")
print(resp.content)
print(resp.usage.total_tokens)
print(resp.structured_output) # populated if output_schema set
Important BaseAgent parameters
| Parameter | Default | Notes |
|---|---|---|
name |
required | unique id |
instructions |
"" |
supports {template_vars} |
model |
settings.default_llm_model |
prefix routes provider |
tools |
[] |
LLM-shaped dicts |
mcp_servers |
[] |
Auto-discovered tool sources |
handoffs |
[] |
[Handoff(target_agent=..., description=...)] |
memory_config |
AgentMemoryConfig() |
search_memories=True / store_memories=True |
output_schema |
None |
Pydantic model |
template_vars |
{} |
static slots |
examples |
[] |
few-shot |
instruction_modifiers |
[] |
dynamic prompt rewriters |
on_start / on_end / on_error / on_tool_call / on_handoff |
None |
sync callables |
config |
AgentConfig() |
max_turns=25, react_mode, reasoning_mode, scanners, strict_security, max_consecutive_handoffs=3 (same request to the same target before HandoffLoopError; fan-out over N items is never blocked), … |
gateway_mode |
None |
Smart Gateway routing: "strict" / "modest" / "quality" |
policy_store |
None |
Access-control store. None = fail-open (no authorization). Use PolicyStore.default_deny([...]) to fail closed; set AgentConfig(strict_security=True) to raise when side-effectful tools have no policy |
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.
- 1mo ago First seen · 152 lines · 74 tokens per session scan A 3914b6816f73
continuum-agent is a skill published in the GitHub repository shyftlabs/continuum (84 stars, last pushed 11d ago), licensed Apache-2.0. It adds 74 tokens to every session and 1,287 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-09-03.
Other skills, from other repositories
api-interface-design
Use when designing public APIs, module boundaries, provider adapters, tool schemas, or data contracts.
theokit-agents
TheoKit agent/LLM integration — agents/.ts convention (AgentBuilder), the tool() builder, capabilities (advanced/DI), useAgent client hook.
theokit-frontend
TheoKit frontend — file-based routing, layouts, theoFetch typed client, useAgent, React patterns.
theokit-config
TheoKit configuration — the config() builder, plugins, security, storage, agents, build targets.
theokit-database
TheoKit database — Drizzle ORM, SQLite schema, migrations, seeds, db commands.
code-review
Perform thorough code reviews, identify bugs, suggest improvements, and explain code quality issues. Use when the user shares code and asks for a review, bug hunt, or quality feedback.