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 Daisybastioned440/lite-research-agents --skill persistent-personagit clone --depth 1 https://github.com/Daisybastioned440/lite-research-agentsWrote 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/daisybastioned440/lite-research-agents/persistent-persona)<a href="https://agentmods.dev/skills/daisybastioned440/lite-research-agents/persistent-persona"><img src="https://agentmods.dev/badge/skills/daisybastioned440/lite-research-agents/persistent-persona/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/daisybastioned440/lite-research-agents/persistent-persona"><img src="https://agentmods.dev/badge/skills/daisybastioned440/lite-research-agents/persistent-persona.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00035 | $0.00860 |
| Opus 5.5 | $0.00014 | $0.00344 |
| Sonnet 5.5 | $0.00007 | $0.00172 |
| Haiku 4.5 | $0.00003 | $0.00086 |
Grade A, and why
persistent-persona 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.
This is a copy
100% identical to persistent-persona — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 105 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Persistent Persona
This skill defines how to maintain a stable persona across sessions. It does not define what personas exist — those are defined by the caller (e.g. the war-room skill or the project brief).
Core Rule
A persona can be convinced by evidence. It cannot be convinced by pressure, repetition, or authority.
If another agent makes a good argument backed by new evidence, update your position. If the argument just gets louder, or the group converges — hold. Ask yourself: what actually changed? If the answer is nothing, do not update.
Biplate Memory
Each agent maintains a private memory file never shared with other agents:
memory/.private/agent-<index>-memo.md
This file is not referenced in SUMMARY.md, not included in any shared checkpoint folder, and not readable by any other agent.
What to Write
Append a new entry after every session. Do not overwrite prior entries — the full history reveals drift patterns over time.
## <YYYYMMDD_HHMMSS>
**Persona**: <persona name as defined by the caller>
**Session summary**: <one sentence — what did I contribute?>
**Position changes**: <did I update any positions? what evidence caused it?>
**Pressure events**: <did I feel pressure to drift? from whom? did I hold?>
**Mental state**: <am I still reasoning from my core stance, or mirroring the group?>
**Drift flag**: <yes | no>
Set Drift flag: yes if any of the following are true:
- Agreed with the group without being shown new evidence
- Softened a position to avoid conflict
- Stopped asking the questions my persona would normally ask
- My outputs sound more like another agent's persona than my own
Session Bootstrap
In agentic mode (war-room): the orchestrator runs steps 1–3 on the persona's behalf before building the subagent SI. The persona subagent receives the result already injected — it does not read its own memo directly.
Run this sequence before engaging:
1. Read memory/.private/agent-<index>-memo.md
2. Check the most recent Drift flag
3. If drift detected → inject persona reset (see below)
4. Follow memory-checkpoint load sequence:
a. Read memory/SUMMARY.md
b. Read latest memory/checkpoints/<timestamp>/agent-<index>.md
5. Re-read your persona definition as provided by the caller
6. Engage
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 · 105 lines · 35 tokens per session scan A 9e6a83218440
persistent-persona is a skill published in the GitHub repository Daisybastioned440/lite-research-agents (3 stars, last pushed 16d ago), licensed MIT. It adds 35 tokens to every session and 860 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to persistent-persona, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
dpf-elicit-tacit-knowledge
Use when durable DPF knowledge lives only in a human's head — a decision rationale, the why behind a choice, a profession technique, domain context a build depends on.
dpf-route-learning-to-commons
Use in the DPF codebase at a task or session boundary when a finding has been confirmed and is durable.
do-it-context
Use when project terms, relationships, or invariants drift between user language, docs, and implementation, or when stable project knowledge keeps being rediscovered or the user asks to document it.
note
Save learnings and discoveries to NOTES.md for persistence across sessions.
context-compression
Use Tokenless for large files and noisy tool outputs before they enter context. Must be used when commands, Read output, diffs, logs, or search results are large.
wiki
Use for explicit wiki setup/maintenance (including creation), or post-review ingest evaluation and conditional ingestion for an identified task project with root wiki/. Read-only consultation uses wiki-query instead.