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 commands/agentsea/flashbacker/personagit clone --depth 1 https://github.com/agentsea/flashbackerWhat 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 | $0.00000 | $0.00395 |
| Opus 5 | $0.00000 | $0.00198 |
| Sonnet 5 | $0.00000 | $0.00079 |
| Haiku 4.5 | $0.00000 | $0.00040 |
Grade B, and why
persona scanned grade B with 1 finding 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.
Unrestricted tool accessmediumExcessive agency
A wildcard tool grant or "run any command" leaves no least-privilege boundary at all.
allowed-tools: "*" What it actually says
🎭 AI Persona System
Apply specialized AI persona templates directly in the current conversation for focused analysis and expertise.
Usage
/fb:persona <persona-name> <your request>
Available Personas
Use flashback persona --list to see current available personas and descriptions
Important: If the persona requested by the user does not exist, return "❌ Persona '{persona_name}' does not exist" and then run flashback persona --list to show available personas. Do NOT proceed with the analysis if the requested persona is missing.
ELSE (if the requested persona exists), proceed with the rest of this command.
Examples
/fb:persona architect review our API design/fb:persona security analyze authentication flow/fb:persona refactorer identify technical debt
Persona Request Processing
Parse the $ARGUMENTS to extract:
- First argument: Persona name (required)
- Remaining arguments: User's request/question (required)
If no persona name provided, show the usage and available personas above.
If persona name provided:
- Read Persona Template: Use Read tool to load
.claude/flashback/personas/{persona-name}.md - Apply Persona: Follow the persona template's guidelines and principles
- Process User Request: Address the user's specific request using the persona's expertise
- Provide Analysis: Give focused analysis based on the persona's specialization
Response Format
When applying a persona:
# 🎭 {Persona Name} Analysis
{Apply the persona template's principles and approach to analyze the user's request}
## Recommendations
{Provide specific recommendations based on the persona's expertise}
Error Handling
If persona file not found, return error message and run flashback persona --list to show available personas dynamically.
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 · 53 lines · 0 tokens per session scan B 4c36927f2e79
persona is a command published in the GitHub repository agentsea/flashbacker (57 stars, last pushed 7mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 395 tokens. A static security scan graded it B with 1 finding (unrestricted tool access). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other commands, from other repositories
git
Git operations with intelligent commit messages and workflow optimization.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.